Introduction

“87% of neighborhoods in San Francisco undergoing gentrification were once redlined as hazardous” (“From Redlining to Gentrification: The Policy of the Past that Affects Health Outcomes Today”). Redlining was a discriminatory practice in which banks and government agencies denied services such as insurance and mortgages to residents of neighborhoods with large African American and other minority populations. Over time, this practice caused significant disinvestment and economic deterioration of neighborhoods it affected, leaving many people in a fixed place of poverty that prevented upward socioeconomic mobility.

Established in 1933 as a part of Franklin Delano Roosevelt’s “New Deal” program to lift the country out of economic depression, the Home Owners’ Loan Corporation (HOLC) provided mortgage relief to homeowners at risk of losing their homes through foreclosure, in order to stabilize the housing market. As a part of this process, the HOLC created numerous residential security maps, grading different neighborhoods A-D (A being a highly secure and desirable neighborhood & D being a hazardous neighborhood) in about 200 different U.S. cities. Though aiming to create stability in the housing market, these letter grades were primarily based upon the socioeconomic, racial, and ethnic makeup of the neighborhoods’ residents, which facilitated the development of discrimination in the U.S. housing market. With the Johnson administration’s passage of the Fair Housing Act in 1968, any means of housing discrimination on the basis of race, sex, familial status, nationality, and disability were prohibited, thereby marking the closure of the HOLC’s rampant redlining practices of the mid-20th century. However, despite the practice’s prohibition, redlining had already caused a large amount of socioeconomic damage on the communities it had impacted, through a ripple effect of discrimination prevalent in many of society’s pillar institutions (ie schooling, employment, healthy food access)

In this paper I aim to answer the following question: What are the long-term economic impacts of 1930s-era HOLC redlining in the San Francisco Bay Area? By focusing on the quantitative relationships between redlining tract coverage and census data of racial demographics, household income, educational access, and employment, this paper aims to quantify the extent of redlining’s association with economic disparity throughout the late 20th and early 21st centuries through distributional impacts, categorical comparisons, and regression analysis.

From conducting distributional, categorical, and regression analyses, there are several patterns that can be concluded about the long-term economic impacts of New Deal-era HOLC redlining in the Bay Area. Firstly, the distributions holistically showed minimal change in shape over time indicating that the economic indicators measured stayed consistent over the course of several decades. This consistency goes to show that the economic impacts caused by redlining are solid and aren’t weak enough to change over time. Secondly, the regression analysis showed a negative relationship between income and redlining tract coverage with an increasing slope magnitude over time and a statistically significant relationship between the two variables indicated by the very low p-values.  

Section 1: Distributional Impacts

To examine the persistent long-term economic impacts of redlining across different HOLC-graded neighborhoods (graded on desirability), I first generated histograms of median household income (1980-2000), unemployment (1980-2000), and white-occupied housing (1980-2020) across HOLC grades A-D, which reveal several long term distributional economic trends.

Histograms were chosen because they allow one to see the persistence or change of these economic patterns over time by noticing a persistence of change in the spread and shape of the census data across HOLC grades. The incorporation of histogram series by time period with the four different grades per serie allows one to see variation within each grade and how the socioeconomic indicator of one grade changed over time relative to another. Each histogram plots the relative frequency of a given census variable across HOLC tracts A-D as defined by the 1930s HOLC redlining maps. By using relative frequency histograms rather than raw count histograms, the distributions are normalized which allows for fair and accurate comparison across grades that have a different number of census tracts. To ensure accurate comparability over time, the relative frequency histogram that plots median household income (1980-200) across HOLC grades A-D were converted from nominal US dollars to real 2020 US dollars using the Bureau of Labor Statistics’ annual average CPI values.

Subsection 1A: Median Household Income

The first socioeconomic indicator is real median household income. This variable measures the typical earning level of all households in a neighborhood, which is a strong indicator of overall economic opportunity in that neighborhood. Because nominal incomes change with inflation, the median household incomes were converted from nominal to real 2020 U.S. dollars using annual average CPI values from the U.S. Bureau of Labor Statistics. 

The first observation that can be drawn from Figure 1.1 is that the shape of the distributions of median household income for each HOLC grade remains approximately the same consistently across all three dates of measure. This indicates that aggregate household income for each grade persisted over the period of measure.

The second observation that can be drawn from Figure 1.1 has to do with the differences in intergrade clustering and spread of the data. Grade A’s distribution has a slight right-skew with a moderately-large income range that persists across the three dates of measure. Moving from the Grade A distribution to the Grade D distribution, the data gradually shifts left with each grade closer to D. Grade D’s distribution shows one, a high level of clustering at the left side of the left side of the histogram and two, an income range that is significantly smaller than that of Grade A’s distribution. These two observations continue throughout the three dates of measure.

From these observations, it can be concluded that Grade A Bay Area neighborhoods have a larger range of median household income values with fewer observations of lower median household income values. This conclusion is in accordance with the inference that those in a grade with greater security and desirability tend to have higher job opportunity, educational access, and healthcare access. The subtle right-skew in Grade A’s distribution indicates that a smaller proportion of tracts have exceptionally high incomes which increases the mean and pulls the distribution’s tail rightward. The gradual leftward shift of the distributions from Grade A to Grade D indicates that as the magnitude of risk assessed by the HOLC for the tracts is inversely proportional to the median household income for the tracts. Moving to Grade D, it can be concluded that tracts judged to have lower security and desirability by the HOLC have a smaller range of median household income values and a high proportion of observations of lower median household income. This conclusion is in agreement with the inference that individuals in this grade tend to have lesser job opportunity, lesser educational access, and lesser healthcare access, traits which undermine ability to achieve high household income.

In addition, the moderately-large range of income denoted in Grade A’s distribution hints at a more discrete but key principle of 1930s HOLC redlining: racial prejudice. As observed in Grade D’s distribution, there was a visible clustering of tracts toward the left of the histogram around the lower income values. Intuitively, this logic should apply to Grade A as well but in an opposite fashion: clustering of tracts toward the right of the histogram around the higher income values. However, in Grade A’s distribution there is a significantly-sized range and spread of income, much larger than that of Grade D’s distribution, indicating that Grade A neighborhoods contained households with a variety of median household income values. From this distributional observation, it can be understood that HOLC redlining grading was deeply influenced by racial prejudice, more so than objective economic data for a lot of the time.

Subsection 1B: Unemployment

The second socioeconomic indicator is percent of civilians unemployed (16+). This variable measures the share of the working-class population per grade that are actively seeking employment but cannot find work. Redlined neighborhoods often see disinvestment and lower amounts of socioeconomic mobility so distributional unemployment is a strong indicator of the severity of redlining experienced by grade.

Similar to the distribution of median household income across HOLC grades, the first observation drawn from Figure 1.2 is that consistently across all three dates of measure, the shape of the distribution for each respective HOLC grade remains approximately the same, with only a few minor shifts, which indicates that unemployment shares for each grade persisted over time. This persistence in unemployment suggests that the socioeconomic division caused by 1930s HOLC redlining has stayed relatively intact in the latter half of the 20th century, with census level unemployment shares continuing to mirror structural inequalities imposed by HOLC redlining maps.

The second observation drawn from Figure 1.2 is concerned with the differences in intergrade clustering and spread of the data as well. Generally, these differences are the same as in Figure 1.1 but a mirror flip. Grade A’s distribution shows high left-clustering, a small right-skew, and a very high proportion of observations on that side of the histogram. Moving from the Grade A distribution to the Grade D distribution, the data gradually gains overall spread/range and magnitude of right-skew while also losing peak height. Grade D’s distribution shows a range and median greater than that of Grade A. This pattern of inter-grade shifting from A to D remains approximately the same over the period of measure.

From these observations, it can generally be concluded that the magnitude of risk assessed by the HOLC for the tracts is directly proportional to the percent of civilians (16+) unemployed for the tracts. The association between these two variables is consistent with the inference that redlined neighborhoods tend to have lower economic opportunity, in this case job access, resulting in a higher unemployment rate in these tracts. While the median percent of civilians (16+) unemployed increases moving from Grade A to Grade D, the magnitude of right skew also increases which means that there is a higher degree of variability in tracts deemed less secure and desirable by the HOLC. Economically, this increase in variability in percent of civilians (16+) unemployed from Grade A to Grade D means that the magnitude of risk assessed by the HOLC for the tracts is associated with a higher degree of economic volatility in the tracts. These tracts that have experienced a high amount of redlining have also seen uneven patterns of disinvestment, reinvestment, demographic/population change, gentrification, industrial restructuring, factors which are greatly responsible for a high variation in unemployment in these tracts. In addition to an increase in magnitude of right skew from Grade A to Grade D, a decrease in peak height is also observed. This means the magnitude of risk assessed by the HOLC for the tracts is inversely proportional to the proportion of observations made. Similar to an increase in spread, a decrease in peak height also denotes a proportional relationship between degree of redlining and degree of economic volatility observed. From a statistical standpoint, the decrease in peak height, or flattening, of the distribution means that a fewer proportion of tracts share a common unemployment rate for civilians (16+). This flattening represents a growing internal heterogeneity suggesting that redlining produced a fragmented and nonuniform economic landscape in the areas it greatly impacted.

Subsection 1.C: White Share

The third socioeconomic indicator is percent of white-occupied houses. This variable measures a specific racial composition of occupied housing units. Historically, redlined neighborhoods in the mid 20th century saw a large amount of urban flight in which primarily caucasian residents departed urban areas for suburban neighborhoods. As a result of this exodus, over time, redlined neighborhoods saw a change in white residents so by measuring this variable, we will see how the magnitude and direction of this change across grades and the fluctuations in change over time. 

Similar to the previous two distributions, the first observation that can be drawn from Figure 1.3 is that across the five dates of measure, the shape of the distribution for HOLC grades A, B, and C remain approximately the same, with only a few minor shifts. This indicates that for these grades, the distribution of percent of white occupied homes persisted over the course of 4 decades. Likewise to the other socioeconomic indicators measured in Figures 1.1 and 1.2 respectively, the persistence of shares of white occupied homes suggests that the census-level outcomes of the racial bias  ingrained into HOLC redlining maps has seen very minimal change in the highly to moderately secure and desirable tracts (A-C), indicating that housing segregation on the basis of race has persisted over time in the Bay Area.

The second set of observations that can be drawn from Figure 1.3 concerns the shape of each grade’s distribution over the period of measure: what the shape means and for Grade D, what a shift in the distribution’s shape means. Firstly, moving left to right from Grade A to Grade D, there is a gradual flattening of the distribution, most significantly moving from Grade A to Grade B, and there is a shift from a right-skew to a left-skew. Moving vertically down the figure from 1980 to 2020, the distributions of Grades B, C, and D see a subtle and gradual increase in aggregate peak height over time. In Grade D, there is a sharp increase in proportion of observations over time at the 7-20% range of the 2020 distribution.

From these observations, it can be concluded that magnitude of risk assessed by the HOLC for the tracts is inversely proportional to the percent of white-occupied houses for the tracts over time. As the HOLC grade declines in security and desirability, the distribution becomes increasingly concentrated toward lower percentage values of white-occupied houses. This inverse association, shown by the shift of a right-skew to a left-skew from Grade A to Grade D in each date of measure, confirms our understanding of HOLC redlining having a basis of racial prejudice, as lower-tier grades and areas with higher levels of redlining tend to have a greater minority demographic and a lower majority, in this case caucasian, demographic. The flattening of the distributions in the earlier dates of measure (1980 and 1990 primarily) indicate an increase in demographic variability as tracts become more “hazardous.” While secure and desirable areas remain racially homogenous with a high proportion of caucasians, areas with lower security and desirability are more racially heterogenous reflecting both racial segregation’s influence in HOLC redlining as well as subsequent population shifts driven by disinvestment and suburbanization. The increase in overall peak height for Grades B, C, and D but retainment of a roughly flat shape relative to Grade A’s distribution indicate that there is a greater amount of census data concerning white-occupied housing moving forward in time, but the demographic trends revealed by this data remain persistent as mentioned in detail above. The sharp increase in peak height in 2020 at the 7-20% range of the Grade D histogram indicates that there is a significantly higher proportion of observations concentrated around the lower percent of white-occupied houses in recent times, a trend that can be explained by “white-flight” and suburbanization. This migratory occurrence is defined as the migration of primarily caucasian residents from urban to suburban areas, which results in the economic degradation of urban areas through decreased funding and overall maintenance.

Section 2: Categorical / Group-Level Comparisons

To further explore the economic impacts of 1930s HOLC redlining in the Bay Area, I used categorical plots to visualize redlining’s impact through median household income and educational attainment across HOLC grades A-D.

Definitionally, a categorical plot allows for comparison of a single numerical variable across four levels of categorical variables, in this case, each level corresponding to a HOLC grade A-D. The important distinction that needs to be made in order to understand what the differences are in the displaying of categorical variables (HOLC grades) is the difference in interpretation over time for the histograms vs. the categorical plots. The histogram focuses on distributional change within a singular HOLC grade over time, which provides insight into intra-grade socioeconomic change over the period of measure. On the other hand, the categorical plot focuses on the change in inter-grade variation over time for a given socioeconomic indicator.  Due to this difference, I chose to incorporate categorical plots to supplement the distributions in order to visualize comparative disparities between HOLC grades.

Furthermore, in connecting the two models, a single bar within a categorical plot can be interpreted like a distribution for the HOLC grade that the bar represents, through the spread of data points within the bar.

Subsection 2A: Median Household Income

The first socioeconomic indicator to be analyzed categorically is median household income (real 2020 USD) across HOLC grades A-D. In the figure that assesses this variable, there are three categorical plots, one plot for each period of measure, 1980, 1990, and 2000 respectively.

The first observation that can be drawn from Figure 2.1 is the clear downward trend from Grade A to D that is consistent across all three dates of measure, with Grade A having the highest peak and Grade D having the lowest peak. The second observation that can be drawn from Figure 2.1 concerns intra-grade variability indicated by the distribution of data points within each HOLC Grade’s bar. Consistently across all three dates of measure, Grade A tracts show the greatest intra-grade variability, indicated by a greater spread of data points within the bar. As the HOLC grade declines however, there is a decrease in intra-grade variability, indicated by the increasing clustering of data points within each bar. The third observation that can be drawn from Figure 2.1 is an increase in the peak height for each HOLC Grade’s bar over time, while the vertical separation between each bar remains approximately equivalent over time. 

From the first observation, it can be roughly concluded that magnitude of risk and insecurity determined by the HOLC and the median household income are inversely proportional for the tracts. This observation is consistent with the basis of redlining, in which redlined neighborhoods saw high levels of disinvestment and economic deterioration, preventing upward socioeconomic mobility for residents of these tracts, therefore explaining why residents of redlined tracts tended to have lower median incomes than those of non-redlined tracts. From the second observation concerning intra-grade variability, the higher levels of variability in tracts deemed less risky and more secure by the HOLC indicate that in these tracts, there is a greater degree of economic opportunity and mobility, providing an explanation for a wider spread in Grade A and a tighter clustering in lower grades, where many residents of redlined tracts are stuck in a lower socioeconomic position and unable to advance upwards. From the third observation concerning the increase in relative heights of each HOLC Grade’s bar over time, we can conclude that across all tracts, redlined or not, general development over the period of measure through technological innovation and globalization promoted the median household incomes for each HOLC Grade. Despite this overall increase, the vertical separation for each catplot between each HOLC Grade remains approximately equivalent suggesting that relative disparities between grades persisted despite overall income growth over the period of measure.

Subsection 2B: Educational Attainment

The second socioeconomic indicator to be analyzed categorically is educational attainment across HOLC grades A-D. This variable will be measured by the percent of adults 25 and older with 4 or more years of college education. In the figure below, there are three categorical plots, one plot for each period of measure, 1980, 1990, and 2000 respectively.

The first observation that can be drawn from Figure 2.2 is the clear downward trend from Grade A to Grade D across all three dates of measure, with Grade A having the highest peak and Grade A having the lowest peak. The second observation that can be drawn is the gradual upward shift in each grade over time, shown by the increasing peak height for each HOLC Grade’s bar. In connecting these two observations, we see that the difference in peak heights between the HOLC Grades decreases over the period of measure, with the bars for Grades B-D increasing by a greater amount than the bar for Grade A, revealing a flattening of the downward trend from Grade A to D.

From the first observation, it can be concluded that magnitude of risk and insecurity determined by the HOLC is inversely proportional to the percent of adults 25 years of age and older with 4 or more years of college education for the tracts. This conclusion aligns with the economics of redlining in which neighborhoods that experienced the negative implications of the practice saw less economic opportunity as well as overall disinvestment in their communities. Tracking back to Figure 2.1, we see that neighborhoods in lower tier HOLC grades have generally a lower aggregate median household income. Due to the aggregate financial status of these neighborhoods, we can infer that one of the reasons that households in redlined neighborhoods saw lower degrees of educational attainment was they comprehensively had less disposable income to spend on privileges like textbooks, tutoring services, or in this case, a college education.

From the second observation, it can be concluded that the moderate to lower tier grades saw upward educational mobility over the period of measure. This pattern can be primarily attributed to neighborhood redevelopment and gentrification throughout the Bay Area, particularly in tracts close in proximity to university centers, like UC Berkeley, or booming industries that have attracted more college-educated residents in search of work on a domestic and international level, like Silicon Valley and the South Bay. Coinciding with these inferences, the Bay Area saw several urban redevelopment projects in parts of Oakland, Emeryville, and San Francisco’s Mission District in which communities experienced infrastructural improvement in housing and schools. In a research report titled Engaging Schools in Urban Revitalization: The Y-PLAN (Youth – Plan, Learn, Act, Now!), authors Deborah L. McKoy and Jeffrey M. Vincent define the Y-PLAN initiative in the context of the urban Bay Area: 

“West Oakland, California, is an industrial area suffering the abandonment and blight common to other neighborhoods after the loss of manufacturing employers, a process that began in the 1950s…Stepping into this environment in 2000 was the Y-PLAN (Youth—Plan, Learn, Act, Now!), a model for youth civic engagement in city planning that uses urban space slated for redevelopment as a catalyst for community revitalization and education reform. Sponsored by the Center for Cities & Schools at the University of California (UC), Berkeley, Y-PLAN facilitates positive community outcomes by partnering graduate student “mentors,” local high school students, government agencies, private interests, and other community parties to work on a real-world planning issue. The Y-PLAN is both a pedagogical tool and a planning studio that addresses specific issues in local communities” (McKoy & Vincent, 2007, p. 1).

Due to the implementation of programs such as the Y-PLAN that educationally mobilized the Bay Area’s youth in impoverished areas, many of these neighborhood areas saw educational improvement reflected by the increasing peak heights for tracts in HOLC Grades B-D in the categorical plot. As a result of the flattening of the downward trend, it can be concluded that the educational disparities within the Bay Area were ameliorated over the period of measure, in part due to youth initiatives and other programs seeking educational improvement.

Section 3: Regression Analysis of Raw Median Household Income

To determine the impact of redlining tract coverage on median household income, I also conducted ordinary least squares (OLS) linear regressions for both the raw and logarithm of median household income as a function of redlining tract coverage from a 1930s HOLC map. While the histograms and catplots provide distributional insight and categorical comparison, respectively, into disparities across HOLC grades, the regression allows for high quantitative precision in determining the extent to which redlining coverage can accurately predict income for a Bay Area neighborhood. More specifically, the categorical plots allowed us to see a general slope trend based on the peaks of each bar, but the regression expands upon this observation by making it more specific numerically.

Because nominal incomes change with inflation, the median household incomes were converted from nominal to real 2020 U.S. dollars using annual average CPI values from the U.S. Bureau of Labor Statistics. The purpose of conducting a log-transformed regression was to linearize the relationship and allow for the slope coefficient to be interpreted as a percent change in income for a one-unit increase in tract coverage.

The two key regression outputs that will be analyzed in this section are slope coefficient and p-values, which together, can assess the magnitude and certainty, respectively, of the relationship between redlining tract coverage and median household income over time. For the raw income model, the slope coefficient is interpreted as the predicted change in real median household income by the OLS regression line per one-unit (or 100%) increase in redlining tract coverage. For the log-transformed income model, the slope coefficient is interpreted as the predicted percent change in real median household income by the OLS regression line per 1.0 (or 100%) increase in redlining tract coverage. Given that the distribution of income is skewed, taking the logarithm of income compresses high-income and low-income outliers, which creates a more symmetric and homoscedastic residual distribution. The patterns observed in the logarithm-transformed regression are largely identical to those observed in the untransformed regression, so I decided to include logarithm-transformed regression analysis in the first appendix of the paper. The p-values for each model (raw income and log-transformed income) represent the probability of observing each respective slope by random chance. A low p-value (less than the alpha level of 5%) indicates that the observed relationship is unlikely due to random chance.

Several neighborhood wealth-related trends can be concluded from OLS regression analysis of raw and log-transformed real median household income (2020 dollars) as a function of redlining tract coverage from 1980-2000. While quantitative, these patterns share similarities with the distributional trends derived from the histograms showing real median household income (2020 dollars) across HOLC grades A-D described in detail earlier in the paper.

Here, our parameter beta represents the true slope of the population regression line relating the explanatory and response variables of redlining tract coverage and raw income respectively. The null hypothesis is that beta is equal to zero and the alternative hypothesis is that beta is less than zero.

Figure 3.1 Raw Income as a function of Redlining Tract Coverage

Figure 3.1 confirms a negative association between income and redlining tract coverage based on the slope coefficients. Firstly, the slope coefficient for the 1980 OLS regression is -15,205.29. This means that for each additional one-unit (or 100%) increase in redlining tract coverage, the OLS regression line predicts about a $15,205.29 decrease in real median household income (2020 dollars) in 1980. Secondly, the slope coefficient for the 1990 OLS regression is -29,742.12. This means that for each additional one-unit (or 100%) increase in redlining tract coverage, the OLS regression line predicts about a $29,742.12 decrease in real median household income (2020 dollars) in 1990. Thirdly, the slope coefficient for the 2000 OLS regression is -46,819.90. This means that for each additional one-unit (or 100%) increase in redlining tract coverage, the OLS regression line predicts about a $46,819.90 decrease in real median household income (2020 dollars) in 2000.

While I noted that the association between income and redlining tract coverage remains negative, from the slope coefficients in Figure 3.1, it can also be observed that the magnitude of the decrease in income increases with each subsequent date of measure. From a graphical standpoint, this can be understood as an initially negative regression line that gets steeper and steeper in the negative direction over time. So what does this mean in the context of redlining? From this observation, it can be concluded that the negative impact of redlining coverage on household income worsens overtime, as the same increase in coverage is met with a greater magnitude of decrease in income over the period of measure. This trend can be best explained by the extensive impact of disinvestment in higher redlined areas. Following the HOLC’s classification of neighborhoods as “hazardous” via their redlining maps, banks and financial institutions chose not to lend money to businesses and individuals, insure mortgages, or fund development in these areas due to the high-risk attributed to these areas by the HOLC. As a result of this lack of financial and infrastructural support from banking institutions, these areas deteriorated over time through an aggregate decrease in property values as well as less socioeconomic mobility and in this case, access to high-paying jobs. Due to the extensive decline of the economic makeup of these areas caused by disinvestment, it makes sense why the slope coefficient of the income vs. redlining tract coverage regression decrease over time.

Figure 3.1 also displays very low p-values that all fall significantly below the general alpha level of 5%. Therefore, we can ascertain a relationship between redlining tract coverage and income. Firstly, the p-value for the 1980 OLS regression with raw income as the dependent variable is  . Assuming that there’s no association between redlining tract coverage and real median household income in 1980, the probability of obtaining a sample of this size and observing a negative relationship between redlining tract coverage and real median household income (2020 dollars) as or more extreme than a magnitude of approximately $15,205.29 per percentage point of redlining tract coverage by random chance is less than approximately   (rounded 0.0002%). Therefore, the OLS regression model provides significant statistical evidence that tracts with higher redlining coverage are associated with lower real median household income in 1980 for this sample. Secondly, the p-value for the 1990 OLS regression with raw income as the dependent variable is  . Assuming that there’s no association between redlining tract coverage and real median household income in 1990, the probability of obtaining a sample of this size and observing a negative relationship between redlining tract coverage and real median household income (2020 dollars) as or more extreme than a magnitude of approximately $29,742.12 per percentage point of redlining tract coverage by random chance is less than   (rounded 0.0008%). Therefore, the OLS regression model provides significant statistical evidence that tracts with higher redlining coverage are associated with lower real median household income 1990. Thirdly, the p-value for the 2000 OLS regression with raw income as the dependent variable is  . Assuming that there’s no association between redlining tract coverage and real median household income in 2000, the probability of obtaining a sample of this size and observing a negative relationship between redlining tract coverage and real median household income (2020 dollars) as or more extreme than a magnitude of approximately $46,819.90 per percentage point of redlining tract coverage by random chance is less than   (rounded 0.0002%). Therefore, the OLS regression model provides significant statistical evidence that tracts with higher redlining coverage are associated with lower real median household income 2000.

The consistently low p-values across all three dates of measure (less than the alpha level of 5%) confirms the high statistical strength between redlining tract coverage as an independent variable and median household income as a dependent variable. Furthermore, this aspect of the regression corroborates the trends observed from the slope coefficients of the decreasing negative association between these two variables, indicating that it is extremely unlikely this relationship occurred by random chance.

Conclusion

From distributional impacts, to categorical plots, to regression analysis, we can conclude several long term economic impacts that vary by extent to which a given census tract was redlined and how it changed over time. With the histograms, we saw that a lot of the economic patterns surrounding income and unemployment maintained shape for a given grade distribution over time indicating that a lot of the economic impacts stayed stagnant over the course of a few decades. With the regression analysis, we saw that the magnitude of negative slope for raw income as a function of redlining tract coverage greatly decreased in the 20 year period from around $30,000 to $42,000 in 1980 and 2000 respectively. With the log transformed regression, the slope coefficients were approximately equivalent for each year indicating that income dropped by the same percentage each year which shows relative stability in the influence of redlining, not due to external factors.

Looking forward, I would love to dive deeper into how gentrification interacts with these socioeconomic patterns of redlining. By definition, gentrification is the process in which a poorer area is infrastructurally improved as a result of a wealthier demographic of people moving in. This economic improvement is seen over time through improved housing, healthcare, and new business. By exploring gentrification in the context of redlining, I would ask whether modern reinvestment in previously redlined areas resulted in economic growth, ameliorating the negative effects of 1930s-era HOLC redlining.

While in this paper, I primarily studied solely socioeconomic indicators measuring the effects of redlining (unemployment, income, racial demographics, etc.), I would be curious to explore more health-related effects of this same era of redlining. By conducting research on food deserts, urban areas with limited access to good-quality fresh food, through measuring, for example, the number of fast food restaurants in a given census tract as well as illnesses through measuring, for example, the number of diabetes occurrences or hospital visits in a given census tract, I would bring in a new dimension of human health and biology in association with the redlining I explored in this paper. 

Bibliography

De los Santos, H., Jiang, K., Bernardi, J., & Okechukwu, C. (2021, May 26). From redlining to gentrification: The policy of the past that affects health outcomes today. Harvard Medical Journal. Retrieved October 28, 2025, from https://info.primarycare.hms.harvard.edu/perspectives/articles/redlining-gentrification-health-outcomes

Jonathan Schroeder, David Van Riper, Steven Manson, Katherine Knowles, Tracy Kugler, Finn Roberts, and Steven Ruggles. IPUMS National Historical Geographic Information System: Version 20.0 [dataset]. Minneapolis, MN: IPUMS. 2025. http://doi.org/10.18128/D050.V20.0

McKoy, D. L., & Vincent, J. M. (2007, June). Engaging schools in urban revitalization: The y-PLAN. Association of Collegiate Schools of Planning. https://doi.org/10.1177/0739456×06298817

Nelson, R. K., Winling, L, et al. (2023). Mapping Inequality: Redlining in New Deal America. Digital Scholarship Lab. https://dsl.richmond.edu/panorama/redlininghttps://dsl.richmond.edu/panorama/redlining.

Appendix A: Regression Analysis of the Logarithm of Median Household Income

While the raw-income regression shows the dollar change in income as a function of redlining tract coverage, by taking the logarithm of income and performing the same regression function, we see the percent change in income as a function of redlining tract coverage for the same three dates of measure. Though not visible from the regression outputs, the log-transformed regression mitigates the effect of outliers and influential points that undermined the strength of the relationship between raw-income and redlining tract coverage, providing us slope coefficients and p-values that are optimal for ensuring an accurate relationship between the two variables.

Here, our parameter beta represents the true slope of the population regression line relating the explanatory and response variables of redlining tract coverage and logarithm of income respectively. The null hypothesis is that beta is equal to zero and the alternative hypothesis is that beta is less than zero.

Figure A1 Logarithm of Income as a function of Redlining Tract Coverage

Similar to the raw income regression, the results of the log-transformed regression shown in Figure A1 confirm a negative association between redlining tract coverage and income as well. The slope coefficient for the 1980 OLS regression is -0.30. This means that for each additional one-unit (or 100%) increase in redlining tract coverage, the OLS regression line predicts about a 30% decrease in real median household income (2020 dollars) in 1980. The slope coefficient for the 1990 OLS regression is -0.28. This means that for each additional one-unit (or 100%) increase in redlining tract coverage, the OLS regression line predicts about a 28% decrease in real median household income (2020 dollars) in 1980. The slope coefficient for the 2000 OLS regression is -0.32. This means that for each additional one-unit (or 100%) increase in redlining tract coverage, the OLS regression line predicts about a 32% decrease in real median household income (2020 dollars) in 1980.

Similar to the raw income regression, the results of the log-transformed income regression evidenced in Figure A1 show very low p-values. Therefore, we can ascertain a relationship between redlining tract coverage and income. The p-value for the 1980 OLS regression is  . Assuming that there is no relationship between redlining tract coverage and the logarithm of real median household income in 1980, the probability of obtaining a sample of this size and observing a linear relationship between redlining tract coverage and the logarithm of real median household income (2020 dollars) with a slope coefficient of -0.30 or less by random chance alone is less than  %. Therefore, the OLS regression model provides significant statistical evidence that tracts with higher redlining coverage are associated with lower proportional levels of real median household income in 1980. The p-value for the 1990 OLS regression is  . Assuming that there is no relationship between redlining tract coverage and the logarithm of real median household income in 1990, the probability of obtaining a sample of this size and observing a linear relationship between redlining tract coverage and the logarithm of real median household income (2020 dollars) with a slope coefficient of -0.28 or less by random chance alone is less than  . Therefore, the OLS regression model provides significant statistical evidence that tracts with higher redlining coverage are associated with lower proportional levels of real median household income in 1990. Lastly, the p-value for the 2000 OLS regression is  . Assuming that there is no relationship between redlining tract coverage and the logarithm of real median household income in 2000, the probability of obtaining a sample of this size and observing a linear relationship between redlining tract coverage and the logarithm of real median household income (2020 dollars) with a slope coefficient of -0.32 or less by random chance alone is less than  . Therefore, the OLS regression model provides significant statistical evidence that tracts with higher redlining coverage are associated with lower proportional levels of real median household income in 2000.

For the most part, these two outputs of the regression reveal largely similar or identical patterns as the raw-income regression. Firstly, the slope coefficients reveal a negative relationship between redlining tract coverage and median household income that steepens over time. This steepening means that the percent decrease in median household income per 100% increase in redlining tract coverage increases with each subsequent date of measure.

Again, the p-values for this regression are far below the alpha level of 5% meaning that a relationship between redlining tract coverage and the logarithm of income is statistically significant across all three dates of measure, and not due to random chance.

About the author

Rishi Haldar

Rishi is a senior at Miramonte High School with interests in economics, mathematics, statistics, and history. He plans to attend Cornell University in the fall, where he will be studying economics in the College of Arts and Sciences. Apart from academics, Rishi is a guitarist in a band that plays local gigs (restaurants, fundraisers, etc.) and plays soccer for a club team and his high school team.

The post Redlining: Quantifying the Economic History of the San Francisco Bay Area appeared first on Exploratio Journal.

Abstract

This paper focuses specifically on terrorism in India, with particular reference to Kashmir insurgency and the Naxalite (Maoist) movement, examining the structural, political and socio-economic factors that contributed to the emergence of these insurgent groups. 

The study is further situated within two principal theoretical lenses identified by Jeff Goodwin: the traditional perspective, which conceptualizes terrorism as a “weapon of the weak”, and the radicalization perspective. In addition, the paper critically reviews the work of prominent scholars whose analysis highlights diverse motivational factors. 

Building on this framework, it also identifies and analyses the principal causes underlying the Kashmir insurgency, highlighting political marginalization, cross-border influence, identity-based grievances, the legacy of the unresolved 1947 Partition dispute, and the impact of Hindutva politics have shaped the trajectory of conflict in the region. 

Extending this analysis, the paper examines the Naxalite Movement (Maoist) movement, tracing its roots to socio-economic inequalities, agrarian exploitation and the persistent marginalization of tribal communities, alongside the ideological influence of contested claims regarding external (particularly Chinese) involvement.

However, in reference to the Kashmir insurgency and the Naxalite (Maoist) movement, Terrorism in India cannot be narrowly confined to religious extremism alone. Rather, it must be understood as the outcome of intersecting structural, ideological and political factors. India’s complex geopolitical location and its history entrenched conflicts have further vulnerabilities in the internal security framework. In light of these findings, it’s important for the enforcement of inclusive governance, credible institutions and sustained socio-economic development to address root causes that perpetuate conflict and instability instead of militarization. 

1. Introduction

What are the causes and consequences of terrorism in India with reference to the Kashmir insurgency and Naxalite movement today? India, like many other countries around the world, has suffered several terrorist attacks over the last two decades. In this research paper, I aim to explore some of the factors that contribute to the rise of terrorism, and to examine its consequences on domestic politics and foreign relations. 

Terrorism has emerged as one of the most persistent and complex challenges in contemporary states, particularly in developing democracies such as India. Several studies identify socio-economic disparities, political exclusion, regional imbalances and perceived injustice as certain factors contributing to the emergence of terrorism. In this model, terrorism is often conceptualized not merely as indiscriminate violence, but as a strategic instrument employed by non-state actors.

Two prominent theoretical perspectives can help in contextualizing the phenomenon. The traditional view portrays terrorism as the “weapon of the weak”, suggesting that downtrodden groups resort to asymmetric violence and in contrast, the radical perspective interprets terrorisms as part of a wider process of escalating political violence, where ideological mobilization, identity-based politics and structured inequalities over the time.

This study points out two major challenges that have continued to shape India’s territorial security landscape: the Kashmir conflict and the Naxalite (left wing extremist) movement. The Kashmir issue represents a multifaceted conflict rooted in historical disputes, regional aspirations and cross-border interactions. Motivations which link to terrorism in this region include separatist aspirations, the influence of global jihadist movement, ideological divergences, perceived political marginalization, etc.

Arising from the 1960s in Naxalbari village of West Bengal, the Naxalite movement reflects a different but also an important form of political violence. Emerging from a radical communist ideology, the movement initially mobilized marginalized rural populations around issues of land redistribution, class exploitation and state neglect

By examining these two cases, this paper seeks to address our central research question: What are the principal causes of terrorism in India? Through a critical analysis of structural conditions, ideological motivations and state responses, the study aims to contribute to an understanding of terrorism as a product of intersecting political, economic and identity-centric factors. This study examines these two cases and offers policy recommendations. 

2. Defining Terrorism

It is important first to define the concept of “terrorism” before addressing my main research question. Terrorism is a highly contested term, and there is no common argument among the scholars on how to define it. However, the purposes of this paper, is to define terrorism in line with Goodwin (2019): “any tactic or set of tactics used by any government, group, organization, or individual, in pursuit of a political goal (broadly defined), which is intended to kill or harm civilians or noncombatants (as opposed to soldiers or political leaders) so as to frighten, intimidate, demoralize, provoke, or pressure other civilians and/or political leaders.” In short, this definition prioritizes that terrorism is primarily about the harming of civilians in order to intimidate others for political ends.

3. LITERATURE REVIEW: CAUSES OF TERRORISM

The section reviews literature on the causes of terrorism, highlighting two major arguments: one links to individual factors like religious fundamentalism and psychological traits while other traces to political marginalization and socio-economic inequalities and ethnic divisions. 

3.1 Individual-Level Explanations: Ideology and Psychology

To start with the first argument, older literature tends to emphasize that terrorists- were motivated by ideology, psychological predispositions, or religious fundamentalism (especially Islamic fundamentalism) (Pape 2003; Kramer 1990; Merari 1990; Post 1990). 

However, Pape (2003) argues that modern day terrorist attacks have not just limited to religious fundamentalists or to isolated men with certain psychological variations, but he gives the example of the LTTE (Liberation Tigers of Tamil Eelam), a group which recruited individuals who were Hindu Tamils but who were inclined towards Marxist ideology.

3.2 Structural and Political Explanations

The second type of argument focuses on some social grievances for example: political – and not religious, or individual psychological – motives of the terrorists. It has highlighted the motives i.e., to achieve specific political motives, change the policies in favour of them, to get financial backing (Crenshaw 2012; Abrahms 2008; Goodwin 2019). Crenshaw (2012) argues that violent acts are intentional political and strategic choices, rather than the inevitable result of social or psychological factors. In her view, terrorism functions as a “weapon of the weak,” used by actors who lack conventional means to influence government policy. Groups such as Euskadi ta Askatasuna (ETA) in Spain and the Provisional Irish Republican Army (PIRA) in Northern Ireland have used violence to pursue ethnic and religious rights Abrahms (2008) similarly argues that terrorism is the last and only resort for some groups to achieve their political goals.

Although the act of suicide terrorism might be irrational on an individual level. Thomas Schelling (1996) may have called it “the rationality of irrationality” – that is, the individual dies but the group is able to strategically demonstrate to the audience that it is serious about its political goals (Pape 2003). Terrorist groups are more likely to use suicide terrorism when there is a possibility of changing public opinion in favour them (i.e., in democracies). In the words of Boix and Rosato (2001): “The target state of every modern suicide campaign has been a democracy. The United States, France, Israel, India, Sri Lanka, Turkey, and Russia were all democracies when they were attacked by suicide terrorist campaigns, even though the last three became democracies more recently than the others.” Crenshaw (2012) similarly argues that terrorists do not just target communist regimes, but also target democracies.

Terrorism is closely linked to social and political conditions that create exclusions and injustice, which can be explained by some contextual examples on socio-political grievances. For example, when a minority group feels isolated in their own homeland, it forces them to retaliate or harm the civilians of their own nation or others. To make it clearer, we can take the example of attacks on Muslim community in India whether in Kashmir, Ayodhya or Godra Kand, which scorn the wounds of the neighbouring states which led to 26/11.  In short, historical rifts are also the causes which never cure the wounds of the nation. 

According to Edward Newman (2006) “These conditions-such as poverty, demographic factors, social inequality and exclusion, dispossession, and political grievances can be either permissive or direct.” This shows how terrorism is directly linked with environmental factors which degenerates the equality, rights and dignity of a human being. Ongoing social inequality and exclusion contribute to perception of injustice, while political grievances and dispossession weaken trust in state institutions. 

Furthermore, Terrorism is closely linked with the failures of human securities which can be understood as a consequence of insecurity and modernization where marginalized individuals resort to violence due to lack of opportunities and social breakdown for which O’Neill (2002) says, “human insecurity, broadly understood, provides the enabling conditions for terrorism to flourish”. As a result, insecurity of a human leads to its action which might harm the community. Also, terrorism is considered as the last resort to accomplish their needs and desires when peaceful methods don’t pay off. To understand with a few examples: Afghanistan, Sudan, Algeria, Yemen, Georgia, Pakistan. Somalia- which are the fundamental core of the operations conducted by the groups all over the world because of poverty.

In accordance with earlier explanations, this perspective offers a different account of the causes of terrorism. As per Martha Crenshaw (2012), she firstly makes a point on Modernization which creates a link between the individuals via easy transportations and communications.   Urbanization is one of the best tools which comes under modernization, as it increases the number of mobility and accessibility of targets and methods, which she termed as “urban guerilla warfare”, which was seen in Latin America in the 1960s.

This approach indicates that terrorism is not just driven by ideology or political grievances but is also shaped by structural transformations in society. Processes such as modernization and urbanization create environments that increase connectivity, mobility and the concentration of targets, thereby making terrorist strategies more feasible. 

4. THEORETICAL FRAMEWORK

Theoretical framework explain terrorism through two perspectives- first is Traditional theory, finds terrorism as “the product of weakness and/or desperation of some rebel or state (a ‘weapon of the weak’)” when there is a lack of capacity in pressurizing their opponent by their non-violent or conventional acts. The second, The Radicalization Perspective, which believes that “not all radicals may be terrorists, but all terrorists are radicals”. Radicalization is understood as “a process leading towards increased use of political violence”. Both theories ultimately points to a common goal i.e. Political motives. (Jeff Goodwin, 2019). Together, these perspectives indicate that terrorism is not merely a tactical choice but also a political constructed strategy shaped by both opportunities. 

5. INDIAN TERRORISM LANDSCAPES

This section focuses on the insurgencies faced by India.  India is a secular and multicultural nation. Since 1947, conflicts with Pakistan have led to wars. The Kashmir dispute emerged after the 1947 Instrument of Accession, leading to prolonged conflict between India and Pakistan. But India is not just facing such insurgencies by Pakistan, internal insurgencies continue which harm the peace and harmony of the nation. Apart from Kashmir related issues there is another big issue, i.e. The Naxalite or Maoist movement began in 1969 in Naxalbari and spread across states.

5.1 On Kashmir Conflict

Historical Background

The Kashmir dispute emerged during the 1947 partition of British India. Princely states were permitted to join either country. Jammu and Kashmir, ruled by Maharaja Hari Singh, had a Muslim-majority population but was governed by a Hindu ruler who initially attempted to remain independent. In October 1947, tribal fighters from Pakistan entered the region, prompting the Maharaja to seek military assistance from India, leading to the first war between India and Pakistan. This conflict was referred to the United Nations, which called for a ceasefire and proposed a plebiscite to allow Kashmir to determine their future. Unfortunately, the plebiscite was never conducted and the region was divided. In Curfewed Night, Basharat Peer presents this history as lived trauma. The memoir briefly outlines the unfulfilled promise of self-determination. Rather than analysing diplomatic negotiations, the book highlights how unresolved political conflict translated into militarization, curfews and insecurities in the Kashmir Valley. Having outlined the historical foundations of the dispute, the discussion now moves to the factors that have shaped the rise and continuity of militant violence in Kashmir. 

Drivers of the Kashmir insurgency

Many possible motives can be drawn for attacks in India, which is provided by K. Alan. Kronstadt (2008, pg. 6), according to some reports, radical Islamic sentiments play a crucial role, as radicals wanted a certain revenge for their Indian Muslim community in Ayodhya, Uttar Pradesh- 1992 and at Godra, Gujarat- 2002. And it is known that the radicals were inspired by Al-Queda’s brand of global jihadi ideology.  Some views indicate LeT has aimed for Kashmir’s separatism as their primary goal.  The Kashmir problem is related to the state’s claim by which state, which was very clearly demarcated since 1947. By military, Line of Control separated Muslim majority Jammu and Kashmir from Pakistan which controlled Azad Kashmir. Secretary Rice has speculated that the goal of the attackers was “probably to stir up trouble between Pakistan and India.” 

Terrorism violence in India cannot be explained by a single ideology; it results from the interaction of religious radicalization, geopolitical rivalries and unresolved territorial disputes. The Kashmir conflict and India-Pakistan tensions provide a strategic environment where extremist groups try to internationalize the issue and escalation between the two states. Thus, terrorism also functions as a strategic tool to influence regional politics.

In line with Shivaji Khemnar (2018), there are ethno-nationalist terrorism, religious terrorism, left wing terrorism, Narco terrorism. Roots of massive terrorism in India, are various in ideology, poverty, regional imbalance, strong worship about religion. India suffers attacks from Bangladesh, Nepal and Pakistan. 

Following this, Vani. K. Borooah (December 2008), provided some factual data of the attacks held in Kashmir. Over the period of 1998-2004, 784 terrorist incidents in India which resulted in 3008 deaths, and 61% of them and 55% of casualties occurred in Jammu and Kashmir alone. Apart from native-born terrorism, Kashmir conflict has attracted Al-Qaeda who have viewed this as a large part of Islamic strategy. A pamphlet titled “Why are we waging jihad” by Lashkar-e-Taiba includes the spread Islam in every corner of India. (Haleen 2004; Borooah 2008). Islamist groups were responsible for 126 attacks out of which 12 were suicidal attacks, out of which 6 were by Lashkar-e-Taiba, 2 were by Al-Mansurian (LeT) and 2 were by Jaish-e-Mohammad.

This is important statistical evidence which shows the concentration of terrorist incidents in J&K, the analysis largely focuses on quantitative data and military group involvement. Hence, the data highlights the scale and external linkages of terrorism. 

The Kashmir revolt is traced from the middle class and their frustration as it lacks employment opportunities (Sumit Ganguly; Prem Shankar Jha). Why do democratic political systems tend to experience higher incidents of terrorist attacks? 

It is explained in the lines “The growth of political assertiveness of minority communities in democratic states is virtually inevitable. As minorities acquire increased literacy and education, they will become more conscious of their political rights and will seek to assert them. Nondemocratic, poly-ethnic states can suppress minority demands for political participation through co-optation, coercion, or repression.” (Sumit Ganguly, 1996). 

Hence, this argument can be interpreted as rising awareness and mobilization especially among educated minorities– can create pressures that political institutions struggle to manage. However, this explanation may overemphasize political participation as a cause of terrorism, while underestimating other factors such as regional, external support to militant groups and state responses. Thus, democratic openness may create space for dissent, but it does not necessarily make democratic the only and primary cause for terrorism. 

Terrorism cannot be explained solely in terms of social and political factors; rather politics plays a crucial role in shaping and concealing issues that are deliberately prevented from being revealed. In Kashmir there are 3-way perspectival divisions: Hindus in Jammu, Buddhist in Ladakh and Muslims in Kashmir and it has created a paradigm that Kashmir is Muslim and is Anti-National. It gives a reflection of the Kashmiris struggle “against India’s brutalities”, where they were illegally detained, tortured, imprisoned and exploited. 

Under the governance of NDA, ideology of Hindutva was followed and spread in Kashmir without considering Muslims in Kashmir, which has resulted in the rise of attack frequency.

Hindutva-driven political strategies have indirectly increased tensions in Kashmir by making many Muslims feel excluded and unheard. Debates around Article 370 and 35A, along with efforts to fully integrate the region have added to this feeling of insecurity. At the same time, the growing support between Hindu nationalist groups and some Kashmiri Pandits has deepened divisions. These tensions and grievances are used by militant groups, which keep the cycle of conflict and violence going. (Mridu Rai, 2019)

Her focus is on political narratives, identity politics, and ideological agendas- particularly debates around Article 370 and 35A- which has shaped perspectives of marginalization in Kashmir. However, this argument primarily emphasizes the role of Bhartiya Janta Party and Hindutva politics. Nevertheless, political factors play a significant role, since politics shapes governance and national decisions-making which remains crucial in understanding terrorism and instability. 

The BJP’s Kashmir Policy: Continuity and Change from Vajpayee to Modi

While the Kashmir conflict is often explained through historical, social and security-related factors, political dynamics also constitute a significant dimension, as political parties frequently shape policies and narratives in alignment with their ideological orientations and strategic interests. 

In line with Mridu Rai (2019) there are 2 eras of the BJP government, which depicts the conditions in the Kashmir valley since the 1990s. According to the report, since 1990 Kashmir has experienced less governance in the conventional sense and more population control enforced through fear and violence. The passage further argues that the Indian state under the Modi government has intensified this security-oriented approach, framing it within the ideological vision of the Hindu Rashtra.

It presents a comparative analysis of the BJP under Atal Bihari Vajpayee and under Narendra Modi, particularly in relation to Kashmir and Pakistan. It suggests that Vajpayee’s tenure represented a relatively peaceful phase in India’s Kashmir policy. Vajpayee included this approach in the slogan “Insaaniyat, Jamhooriyat aur Kashmiriyat”, signalling a framework attached with humanity, democratic process and recognition of Kashmir identity.

In contrast, the Modi government has described as adopting a more assertive and militarised way toward Pakistan. Public celebration of “surgical strikes” and repeated warnings of retaliations show increased aggression. This external posture is said to be mirrored internally in Kashmir, where stronger security measures have been justified in the name of countering cross-border terrorism. 

 It argues that organisationally, the BJP has undergone significant transformation since 2014. While centralized under Vajpayee, but more monolithic under Modi’s leadership, with reduced space for internal dissent and increased subordination of regional leadership to central command. Since 2014, the author suggests, incidents of hostility and violence against such groups have been more visible. 

Cross-border Militancy in Jammu & Kashmir

Numerous attacks in Kashmir are observed, like Mumbai Train Blast (2006), Mumbai Attack 26/11(2008), Mumbai Bombing (2011), Pathankot Airbase Attack (2016), Uri Attack (2016), Pulwama Attack (2019), Bengaluru Attack (2023), Pahalgam Attack (2025). 

The most recent Pahalgam attack (22nd April 2025), which resulted in the death of 27 security personnel and injury to over 40 civilians (Adil, Sohail & Farid, 2025).  Pahalgam was a core of tourism along with the transit point for Annual Amarnath Yatra pilgrimage, which was then considered as the attack on for both its scale and its symbolism. By the Indian Ministry of Home Affairs, Pakistan’s military group Lashkar-e-Taiba was accused of this insurgency. (Tanveer, 2025). This time India retaliated with fearlessness by its operation named “Operation Sindoor” on 7 May 2025.

The paragraph concludes with the call of, that Kashmir has been called by Arundhati Roy, a ‘real theatre of unspeakable violence and moral corrosion.’ (Muhammad Feyyaz 2019). Geopolitics plays a significant role with all events happening in and around the world. Geography is what stabilizes or destabilizes a nation’s security and development. Pakistan’s desire to cover Kashmir in its territory is not just in the interest of Islamic fundamentalism, instead, its geographical, hydrological and strategic factors. It is important for Pakistan to maintain a powerful position in Kashmir, essentially for water security and advantageous position against India.  

Repercussions of Armed insurgency

Since 1947, this prolonged conflict in Jammu and Kashmir has had wide- ranging impacts beyond security. It has led to environmental damage, economic decline (majorly tourism), has disrupted education and regular life, along with serious mental health issues as per Dr. Mushaq Margoob, Professor & Head, Post Graduate Department of Psychiatry, Government Medical College, Srinagar. Taken together, these have weakened the region’s social and economic stability. Overall, terrorism has deeply affected Kashmir’s development and the life-style of the people. 

5.2 THE NAXALITE (Maoist) MOVEMENT

Historical Background and Origins

After examining the conflict in Kashmir, it is equally important to turn to another major internal security challenge persisting in India–the Naxalite Movement. The Naxalite movement, also known as Maoist insurgency in India, originated in 1967 in the village of Naxalbari in West Bengal as a radical peasant uprising against those land inequalities and exploitative agrarian structures. Inspired by Maoist ideology and the principles of the armed revolution, the movement sought to challenge what is known as a semi-feudal and oppressive state system. The movement was ideologically influenced by revolutionary doctrine linked with Mao Zedong and political development in China during the 1960s. However, this was largely evolved as a domestically rooted response to socio-economic inequalities, tribal marginalization and governance deficit within India. Initially driven by demands for land redistribution and social justice for marginalized communities–which then gradually expanded into the central and eastern parts of Indian states, forming what is often referred to as the “Red Corridor”. Over the period of time, the movement evolved from localized agrarian resistance into an organized armed insurgency. Manohar Parrikar Institute for Defence studies and Analysis (2010) states that the Naxalite movement was driven by radical Marxist- Leninist ideology which led to the formation of the CPI (M-L). Multiple internal challenges seen in: the Central-Eastern area (Red Corridor), North-East India by groups like NSCN & ULFA. (Aditya Dasgupta, Kishor Gawande and Devesh Kapoor; 2017)

Understanding the structural and immediate causes that helps in the emergence and persistence of this movement becomes essential to comprehend its relevance in India’s internal security landscapes. 

Structural and Socio-Economic Determinants

In 2008, Prime Minister-Manmohan Singh described Naxalism as “the greatest threat to our internal security”. The pace of the Naxalite movement suggests not merely state incapacity, but deeper structural contradiction within India’s developmental model, has been the driving force to such insurgent acts. While the Indian state pursued parliamentary democracy and economic modernization, large parts of rural and tribal populations remained excluded from land reforms, political representation, and access to justice. 

In line with European Foundation for South Asian Studies Publications: Naxalbari, the village that gave its name to the movement, was the site of the peasant revolt, started by communist leaders against owners of the state. The Naxalbari uprising was not a mere reason for agrarian anger but an ideological rupture within Indian communism. It marked a rejection of parliamentary gradualism and signalled the re-emergence of revolutionary violence as a legitimate political instrument among sections of the left. Members of Communist Party of India (Maoist), notably Charu Majumdar, Kanu Sanyal and Jangal Santhal who initiated this movement. Drawing inspiration from Maoist ideology, these leaders advocated a strategy of long armed struggle aimed at overthrowing the existing socio-economic order through agrarian revolution. The uprising reflected a vision articulated by the so-called “Siliguri Group”, which called for a militant path to political transformation. The formation of CPI in 1925 institutionalized communist ideology in India drawing inspiration from the global Marxist-Leninist movements and adapting them to the colonial Indian context. In its early years, the CPI was committed to a Marxist-inspired mass revolution but later faced internal and external pressures that reshaped its strategy. In 1951, after consultations with Stalin- who advised participation in democratic politics rather than armed revolt–the CPI reconsidered its revolutionary path. The ideological reshaping laid the groundwork for subsequent fractions within the left movement ultimately which contributed to the emergence of radical Maoist. Disillusionment with the CPI’s gradual and pro-soviet orientation- particularly its commitment to parliamentary democracy and perceived abandonment of revolutionary militancy–led to the break away at the Seventh Party Congress in Calcutta. The CPI-M thus emerged as a distinct political formation that rejected what it characterized as soviet “revisionism” and aimed to reaffirm a more orthodox and militant Marxist line, drawing ideological inspiration from the Chinese Communist model. 

Naxalite emerged as a radical response to deep rooted socio-economic inequalities. Its primary causes according to Sanjay Seth (1995), were as follows: The very first is, Structural Contradictions of Capitalist Development- Capitalist expansion generates contradictions between socialized productionand private appropriation leading to crises which intensify exploitation and weaken legitimacy, creating conditions for resistance.Second is seen as the Formation and Organization of the Proletariat- capitalist modernization concentrates workers in the factories and cities, fostering class solidarity and collective resistance and also creates a basis for revolutionary mobilization. Moving forward, Marxist Reorientation towards Peasant Agency in ‘Backward’ Societies- Marxist revolutionary theory shifts emphasis to peasant agency in backward societies, viewing peasant struggles against feudalism as a key driver for revolutionary change.Along with that Gap between Consciousness and Marxist Political Objectives- Peasant resistance, shaped by local and traditional identities, which differ from Marxist class ideology, creating a gap that leads to ideological tensions. In addition to the initial factors, Misrecognition of Peasant Subjectively by Communist Parties- where communist parties misread peasant consciousness, projecting revolutionary intent, leading to a strategic and ideological disconnect. And last but not the least, Instrumentalization of Peasant Struggles by Vanguard Parties- communist parties often used peasant struggles for their own goals, directing movements beyond peasants’ intent, leading to dissatisfaction.

While Sanjay Seth highlights contradictions between peasant consciousness and Marxist political objectives, the Naxalite movement demonstrates how ideology and lived experience interact dynamically rather than mechanically. Peasant resistance in India was not purely “false consciousness” nor fully revolutionary; rather, it evolved through local grievances–land alignment, state repression and caste hierarchies–that were gradually reframed within Maoist political language. Thus, the movement’s radicalization can be understood as a process of ideological translation.  

It follows that the persistence of Naxalite exposes the gap between India’s procedural democracy and substantive socio-economic justice, particularly in marginalized regions such as Chhattisgarh and Jharkhand. Governance failures, extractive development and weak reforms lead the insurgent appeal, framing it as internal security issues. The growth of Naxalism reflects deeper structural inequalities in India’s development model rather than only a security issue.              

Integrated approaches to mitigate Naxalite insurgency

Although the Naxalite insurgency has emerged from the multiple structural and socio-economic causes discussed above, the Indian government has also introduced several strategies to mitigate the movement. In line with Manohar Parrikar Institute for Defence Studies and Analyses (April, 2010) The Government of India, has adopted a two-pronged strategy, to address Naxalism, combining security measures and governance interventions.The government set up an Empowered Group of Ministers, a Coordination Centre, and a special task force to improve coordination. It focused on a Law-and-Order Approach through police modernization and long-term deployment of centre forces, with the centre bearing costs (around  ₹1,100 crore) to support states. Another approach the government adopted is Social Integration Approach, focusing on development through schemes like the Backward District initiative and BRGF, allocating funds to affected areas. It also implemented state-level support and infrastructure programs like PMGSY to improve living conditions and reduce Naxal influence. 

Sino- Maoist connections

After examining the internal causes and state responses to Naxalite insurgency, it also becomes important to assess whether external factors contribute to these insurgent activities. This analysis helps determine whether policy responses should extend beyond domestic measures to include broader strategic and foreign policy considerations. 

There are two principal stands of argument, one contends that China has no involvement with Naxalite or Maoist movement in India, while the other claims that China bears responsibility for supporting or facilitating these insurgencies.

First argument notes, Maoist groups’ linkages with militant, Northeast insurgent, and radical Islamist organizations for logistical support pose a significant internal security challenge to India, while multiple factors suggest Chinese involvement in sustaining Left-Wing Extremism (LWE). An analysis by the Vivekanand International Foundation quotes The Home Secretary, G.K.Pillai in November 2009, where he was confident with the supply chains of arms by China to Maoists in India, “Chinese are big smugglers and suppliers of small arms. I am sure that the Maoists also get them.”

The Home Minister, P. Chidambaram, acknowledged that Naxalites procure weapons through cross-border routes via Nepal, Myanmar, and Bangladesh, but expressed uncertainty regarding any direct assistance from Chinese state actors. Nevertheless, repeatedly Chinese made arms and communication equipment from Maoist cadres are often cited as indicative of possible linkages between Maoist groups and China. 

To line RSN Singh (2010), the Home Secretary has asserted that China is a major supplier of small arms and suggested that Maoist Groups may procure weapons of Chinese origin. In 2004, a significant supply of light and medium machine guns and ammunition were seized at Chittagong port in Bangladesh, reportedly sourced from China. Bangladesh intelligence officials further alleged that leaders of United Liberation Front of Asom and National Socialist Council of Nagaland (Isak-Muivah) visited Kunming to obtain arms, some of which were allegedly routed to Maoist groups operating in Nepal and India. 

Second, it argues that China has nothing to do with any insurgency, according to the statement issued by the Ministry of External Affairs (May 17, 2012) that India raised concerns with China regarding reported support for anti-India armed groups, prompting China to assure a policy of non-interference and deny such support. China has officially denied supporting anti-government forces and emphasized its policy of non-interference; the dialogue mechanism indicates that India remains cautious and will continue to monitor dimensions of internal threats.

6. Conclusion

In conclusion, the study demonstrates that terrorism is a complex and evolving phenomenon that cannot be understood through a single framework. The discussion of various scholarly definitions, theoretical perspectives and the examination of cases such as Kashmir and Naxalite illustrate that terrorism emerges from the interaction of ideological, political, socio-economic, and historical factors, earlier, terrorism was often narrowly associated with religious extremism; however, contemporary conflicts increasingly reveal an overlap between terrorism and civil wars. This growing convergence has created distinguish terrorism from other forms of political violence, consequently, the absence of a universally accepted and precise definition of terrorism continues to challenge the international community in formulating consistent responses.

From the Indian perspective, geography plays a dual role. While India’s geographical position has historically facilitated cultural exchange, economic interaction and strategic connectivity. It has also exposed the country to security vulnerabilities and cross-border tension. In addition to these historical and geographical factors, ideological influences have also shaped certain forms of insurgency in India. The influence of socialism and communalism, particularly in regions characterized by socio-economic disparities and governance gaps, has contributed to the emergence of structural grievances, including poverty, land alienation and the neglect of marginalized communities. 

The findings of this research suggest that addressing terrorism requires a multidimensional approach. While security measures remain important, long term solutions must also focus on ensuring inclusive development for all sections of society. Future research should therefore explore innovative perspectives that move beyond purely historical explanations and instead examine how structural reforms, effective governance and socio-economic justice can help mitigate the conditions that sustain violent movements. 

Although the complete eradication of terrorism may be unrealistic, meaningful progress can still be achieved through stronger international cooperation, stricter accountability for states that have terrorist networks, and institutional reforms. Finally, the persistence of terrorism highlights not only individual responsibility but also government failures. When the government is unable or unwilling to address citizens’ aspirations and grievances, extremist ideologies find space to grow. In this context, terrorism may be defined as “a strategic and radical practice aimed at influencing state policy through coercion or violence.” 

References

  The Oxford Handbook of Terrorism. (2019). United Kingdom: OUP Oxford.

  Golder, B., & Williams, G. (2004). What is “Terrorism”? Problems of Legal Definition (SSRN Scholarly Paper No. 1351612). Social Science Research Network.

Pape, R. A. (2003). The Strategic Logic of Suicide Terrorism. American Political Science Review, 97(3), 343–361.

Chapter- THE LOGIC OF TERRORISM, Terrorist behaviour as a product of strategic choice by MARTHA CRENSHAW

Terrorism Studies: A Reader. (2012). United Kingdom: Routledge.

 Abrahms, M. (2008). What terrorists really want: Terrorist motives and counterterrorism strategy. International Security, 32(4), 78-105 

Kronstadt, K. A. (2008). Terrorist attacks in Mumbai, India, and implications for US interests (No. CRSR40087).

 Khemnar, S. (2018). Causes and effects of terrorism in India: An overview. International Journal of Applied Information Systems, 12(15), 29-32.

 Panda, J., & Pankaj, E. (2025). Proxy Wars and Silent Partners: The Pahalgam Attack.

Gaibulloev, K., & Sandler, T. (2008). The impact of terrorism and conflicts on growth in Asia, 1970-2004 (No. 113). ADBI Discussion Paper.

  Ullah, A., Qingxiang, Y., Ali, Z., & Anees, M. (2018). Terrorism in India as a Determinant of Terrorism in Pakistan. Asian Journal of Criminology, 13(1), 57-77.

  Saeed, K., Khan, N. A., Arif, I., ur Rehman, A., Rehman, M., & Maheen, N. (2025). FROM PAHALGAM TO CEASEFIRE: THE 2025 INDIA–PAKISTAN CONFLICT, ITS HISTORICAL ROOTS, AND DONALD TRUMP’S MEDIATION ROLE. Pakistan Journal of Social Science Review, 4(4), 1173-1204.

 Ganguly, Š. (1996). Explaining the Kashmir insurgency: political mobilization and institutional decay. International Security, 21(2), 76-107.

Mukherjee, S. (2018). Colonial origins of Maoist insurgency in India: Historical institutions and civil war. Journal of Conflict Resolution, 62(10), 2232-2274.

Rai, M. (2019). Kashmiris in the Hindu Rashtra. Majoritarian state, 259-280.

 Seth, S. (1995). Interpreting revolutionary excess: The Naxalite movement in India, 1967–1971. Modern Asian Studies, 29(1), 205–229. https://doi.org/10.1017/S0026749X00016123 

Singh, R. S. N. (2013). Is China waging a proxy war through the Maoists? Indian Defence Review, 28(2).

Peer, B. (2010). Curfewed night: A frontline memoir of life, love and war in Kashmir.

 https://www.un.org/en/global-issues/countering-terrorism

  https://www.efsas.org/publications/study-papers/economy-and-ecology/

 https://www.wider.unu.edu/publication/prolonged-effects-terrorism

https://www.researchgate.net/profile/Sanjay-Seth/publication/249879533_Interpreting_Revolutionary_Excess_The_Naxalite_Movement_in_India_1967-71/links/5f7b476992851c14bcaf0ddb/Interpreting-Revolutionary-Excess-The-Naxalite-Movement-in-India-1967-71.pdf

Britannica, T. Editors of Encyclopaedia. (n.d.). Naxalite. In Encyclopaedia Britannica. Retrieved [Date], from https://www.britannica.com/topic/Naxalite

Srikakulam peasant uprising. (n.d.). In Wikipedia. Retrieved [Date], from https://en.wikipedia.org/wiki/Srikakulam_peasant_uprising

South Asia Citizens Web. (n.d.). The Naxalite movement: Background and developments. Retrieved [Date], from https://www.sacw.net/article1622.html

International Socialism Journal. (n.d.). The ironies of Indian Maoism. Retrieved [Date], from https://isj.org.uk/the-ironies-of-indian-maoism/

 Political Science Institute. (n.d.). Naxalbari uprising: Genesis of Naxalite movement in India. Retrieved [Date], from https://polsci.institute/india-democracy-development/naxalbari-uprising-genesis-naxalite-movement-india/

https://www.vifindia.org/article/2011/march/25/China-Naxalite-linkages-Gauging-its-dimensions

https://www.mea.gov.in/articles-in-indian-media.htm?dtl/19721/Q598+China+Aiding+Insurgency+in+North+Eastern+States

Source: MP-IDSA https://share.google/ZTQOuCwQstdTYhuLy

Source: EFSAS https://share.google/U55MzH7Zm8dnOYYlH

Source: Vivekananda International Foundation (VIF) https://share.google/LpfQkGBjOJUAXfhgx

ACKNOWLEDGEMENT

I would like to express their sincere gratitude to Dr. Mashail Malik, Assistant Professor, Harvard University for her invaluable guidance, intellectual support, and constant encouragement throughout this research. I also thank her for the insightful discussions and helpful feedback on the initial drafts of this manuscript.

I am grateful to the Department of Political Science at Banasthali Vidyapith for providing the necessary institutional resources to conduct this study.

On a personal note, I wish to thank my parents and friends for their unwavering moral support, patience, and encouragement during the course of this work. Their belief in my efforts was a constant source of motivation.

Finally, I thank the anonymous reviewers for their constructive comments and suggestions, which significantly contributed to improving the quality of this paper.

About the author

Disha Tyagi

Disha Tyagi is currently pursuing a Master’s degree in Political Science from Banasthali Vidyapith. Her academic interests revolve around International Relations, South Asian regionalism, geopolitics, diplomacy, public policy, global governance, trade relations, conflict studies, security studies, and international cooperation. Among these, terrorism and regional instability remain one of her strongest areas of interest and research. She is particularly interested in studying how terrorism impacts regional integration and development, especially in areas such as Kashmir and Left-Wing Extremism in India.

Her academic journey has been enriched through active participation in seminars, conferences, webinars, debates, and international academic engagements. She attended the BRICS International School: New Generation in March 2026 and participated in the Global Studies Program organized by the Russian Federal University in February 2026. She also attended the seminar on “WTO MC14 Outcomes: Future of Multilateralism and Implications on India’s Trade Agenda” held on 5 May 2026, which deepened her understanding of trade diplomacy and multilateral institutions. Additionally, she participated in webinars such as “The Structural Causes of World Poverty” by Thomas Pogge on 23 April 2026 and “India’s BRICS Presidency 2026” by Antara Ghosal Singh on 8 May 2026. These academic interactions enhanced her understanding of global justice, development politics, and emerging geopolitical transformations.

Beyond academics, she has actively participated in Model United Nations and parliamentary simulations, including the Youth Parliament (UNGA Portfolio) held during SANSAD 2025 in Delhi. She has also completed online courses including “Successful Negotiation: Essential Strategies and Skills” by the University of Michigan, “Learning How to Learn” by the University of Arizona, and “Writing in the Sciences” from Stanford University, along with an offline communication course at the British Council, Delhi.

The post From Global Causes to Local Realities: Terrorism in India with Reference to Kashmir and the Naxalite Movement appeared first on Exploratio Journal.

Abstract

Dissociative identity disorder (DID) is a treatable mental disorder that has a proven neurochemical basis. However, public misunderstanding prevents patients from getting appropriate and timely treatment, and medication focusing on dissociation is limited. Therefore, this paper proposes an approach of delivering JDTic and paroxetine by lipid nanoparticles (LNP) through the intranasal route. JDTic and paroxetine target the dysregulated neurotransmitter system. LNPs improve delivery efficacy by increasing bioavailability and drug stability. The intranasal route was chosen as the administration route for its ability to target the brain directly. Limitations and development visions are discussed to inspire further research. 

1. Introduction

DID is a mental illness that affects approximately 1% of the general population. Studies suggest that it is strongly related to severe childhood trauma, most often caused by caregivers. Typical symptoms include subjective experience of identity alteration, memory gaps, frequent experience of depersonalization, along with post-traumatic stress disorder, depression, and anxiety (Purcell et al., 2024). Due to the special symptoms it displays, the disorder and DID patients are receiving public attention, yet few people know the scientific facts about the disease, which has led to misunderstandings about DID patients. This mental disorder has been proven to be treatable, with multiple reported structural and neurochemical basis. However, current medication mainly targets the depression and anxiety symptoms of DID, and focuses less on its dissociations, which are the symbolic symptoms. This study aims to discuss DID from a biological perspective and dive into its dissociation aspect. 

In this paper, we explored a new way of DID treatment. We targeted the opioid system and serotonergic system, whose dysregulations are believed to be the main cause of dissociation. Medications are chosen according to the targeted receptors, namely JDTic for opioid receptors and paroxetine for serotonin receptors. Lipid nanoparticles are then designed to deliver the drugs to the brain. We proposed to administer the drugs intranasally, which was reported to target the brain through olfactory neurons, circumventing the blood-brain barrier (BBB). This could enable more efficient drug administration as well as reduce systemic side effects. Furthermore, we envision several directions related to the theme of this paper. Future studies in these directions could improve medical treatments for DID. We hope to provide new insight into treating this mental illness based on its neurotransmitter basis.

2. The Neurotransmitter Basis of DID

The dissociative symptoms of DID are related to multiple neurotransmitter systems. In this section, we will discuss two neurotransmitter systems that are believed to contribute to dissociative experiences (including depersonalization, derealization, amnesia, etc.), namely the opioid system and the serotonergic system. 

2.1.Opioid System

The opioid receptors are a kind of G protein coupled receptors (GPCR). The system regulates multiple biological and cognitive processes, such as nociception, analgesia, endocrine and immune functions, stress and emotions, and more (Reeves et al., 2022). Opioid receptors are differentially expressed throughout the brain, with higher concentrations in the cortex, limbic region (including amygdala, hippocampus, hypothalamus, and cingulum gyrus), and brainstem (Purcell et al., 2024) . The receptors are categorized into three subtypes: mu (MOR), kappa (KOR), and delta (DOR). The subtypes accept different signaling peptides (Reeves et al., 2022). Exposure to stressful stimuli activates kappa opioid receptor (KOR) signaling, a process known to produce aversion and dysphoria and related to stress-related disorders(Jacobson et al., 2020). A study conducted on nine adult volunteers suggests that enadoline, a kind of KOR agonist, leads to confusion, dizziness, visual distortions, and depersonalization reported by participants (Walsh et al., 2001). Other related studies also suggest that salvinorin is a KOR agonist that relates to depersonalization (Roth et al., 2002). This might indicate that kappa-opioid receptors might be helpful in regulating certain dissociative symptoms. While naloxone, naltrexone, and nalmefene were reported to reduce the dissociative symptoms, these therapeutics have yet to be systematically studied, and conflicting results were shown in recent studies (Purcell et al., 2024). Therefore, we propose JDTic, an alternate medication that targets the KOR, thus in theory can alleviate dissociation. 

2.2.Serotonergic System

The serotonin receptors can be classified into six different GPCR populations (namely 5-HT₁, 5-HT₂, 5-HT₄, 5-HT₅, 5-HT₆, and 5-HT₇) and one family of ligand-gated ion channels (5-HT₃). Every receptor class regulates neural processes through a different mechanism. Under each class, they can be further divided into specific subtypes, each of which has a different function, agonists, and antagonists (Pytliak et al., 2011). The receptors are distributed throughout the brain, regulating affect, cognition, autonomic, and other behavioral activities (Purcell et al., 2024). Sixty-seven subjects received depersonalization ratings after double-blind, placebo-controlled experiments with the partial serotonin agonist meta-chlorophenylpiperazine (m-CPP). Results show that m-CPP significantly induced more depersonalization than the placebo did (Simeon et al., 1995). Another study performed a positron emission tomography scan on a patient with dissociative amnesia. Images were compared between the patient in amnestic state and recovery state and 14 other healthy subjects. The patient in the recovery state displayed significantly higher 5-HT_1A receptor bindings than healthy subjects in multiple cortical regions (Kitamura et al., 2014). This might indicate that the serotonin system is possibly related to dissociative experiences. Study suggests that paroxetine, a selective serotonin reuptake inhibitor, might relieve dissociation. 

3. Possible Therapeutics

In this part, we mainly give two medications that seem promising in dissociation treatment and introduce their mechanisms and metabolism. Namely, we will introduce JDTic and paroxetine, targeting the opioid system and the serotonin system, respectively. 

3.1.JDTic

Currently, JDTic is not used clinically. Therefore, we only discuss it as a possible treatment of dissociation due to its medical mechanism. Further study is still needed to enable its clinical application. JDTic is a kind of highly selective competitive antagonist of KOR. Notably, it is not derived from the opiate class of compounds. The potent and selective κ antagonist properties can be explained by the “message−address” concept, a theory that explains the interaction between the ligand and receptor. The “message” component of the ligand specifies primary receptor recognition, and the “address” portion enables selectivity by specifically recognizing a particular receptor subsite (Thomas et al., 2003). 

After JDTic was intraperitoneally administered to mice, its brain level peaked within 30 minutes and declined gradually over a week. JDTic did not show high lipophilicity, demonstrating high water solubility and low distribution into octanol. Brain homogenate binding was within the range of many shorter-acting drugs. JDTic displayed P-glycoprotein (P-gp)-mediated efflux. The surprisingly slow elimination of the drug is postulated to result from the drug lingering in cellular compartments such as lysosomes (Munro et al., 2012).

There is no current evidence that directly proves that JDTic is effective in dissociation treatment. Being an opioid receptor antagonist, JDTic is believed to restore neuron functions that were overly inhibited by opioid receptors. Considering the relationship between opioid receptors and dissociation symptoms mentioned above (KOR especially), it is reasonable to conclude that JDTic might be conducive to dissociation treatment. However, further researches are needed to validate this assumption.

3.2.Paroxetine

Paroxetine is a drug for a variety of anxiety disorders. It is worth emphasizing that in the treatment of PTSD, there are only two approved pharmacotherapies based on SSRIs, including Sertraline and Paxil (paroxetine hydrochloride). It is a potent, selective serotonin reuptake inhibitor (SSRI). It exhibits the highest known binding affinity for the central site SERT compared to any other currently prescribed antidepressants. Paroxetine acts on the serotonin transporter (SERT) in the CNS, which is a type of monoamine transporter that transports serotonin from the synaptic cleft back to the presynaptic neuron. Inhibiting the SERT increases the serotonin concentration in the synapse, enhancing the activation of postsynaptic receptors.

Paroxetine hydrochloride salt ingested orally is almost completely absorbed, with only 2% of the dose recovered in feces. Its absorption was insusceptible to the influence of food or concomitant antacid treatment. It reaches saturation during the pass through the liver. With repeated administration, the steady-state concentration of the drug is achieved within 4 to 14 days. There is no further accumulation of the compound. The distribution of paroxetine in the body is extensive, aligning with its lipophilic amine character, with only 1% of the drug remaining in systemic circulation. After administered intravenously, the volume of distribution ranges from 3.1 to 28.0 L/kg. The mean elimination half-life is estimated to be about 21 h. Almost two-thirds of the drugs are eliminated through the kidneys. Up to 95% of the drug is bound to proteins, mainly P-gp, which is involved in transportation through the blood–brain barrier (BBB) (Data from reference (Paroxetine—Overview of the Molecular Mechanisms of Action, n.d.)(Paroxetine—Overview of the Molecular Mechanisms of Action, n.d.)). 

Paroxetine is mainly metabolized by cytochrome P450 family 2 subfamily C member 19 (CYP2C19) and CYP3A4, producing a catechol metabolite (Benedetti et al., 2009). It is one of the most potent inhibitors of CYP2D6 and CYP2B6, members of the CYP450 family, among SSRIs (Paroxetine—Overview of the Molecular Mechanisms of Action, n.d.). Autoinhibition is observed in the metabolism of Paroxetine, which means that some drugs can inhibit the enzyme(s) involved in its metabolism. When autoinhibition occurs, observed plasma concentrations are higher than the value expected by linear accumulation, which could cause adverse effects or an enhanced therapeutic effect (Benedetti et al., 2009).

In a study conducted to determine the efficacy of paroxetine on PTSD symptoms, results show that paroxetine continued to perform superior to placebo in reducing dissociations during the 12-week maintenance phase. Specifically, significantly more patients treated with paroxetine were rated as responders compared to patients treated with placebo. Mixed effects models showed greater PTSD feature reductions in the paroxetine groups than the placebo groups. Paroxetine was also superior to placebo in reducing dissociation and self-reported interpersonal problems (Marshall et al., 2007). This suggests that paroxetine is a promising medication against dissociation. 

4. Lipid Nanoparticle

To deliver therapeutics for DID to the brain, there are multiple approaches used. The use of lipid-based nanoparticles first came from the biocompatible concept, where the tiny lipid cholesterol molecules and phosphatidylcholine are popular. Lipid-based nanoparticles enable easy cellular uptake of drugs because of the lipid coat. Two of the most important lipid-based nanomaterials are liposomes and solid lipid nanoparticles (SLN). Liposomes are composed of lipid bilayers and enclosed aqueous cores, while SLN consists of a lipid monolayer enclosing a solid lipid core. While they are slightly different in structure, both can be effectively used in drug delivery applications, and nasal administration studies on both types of nanoparticles have been done (Trapani, A et al., 2021). According to existing research, we propose that the medication for DID could be delivered by lipid nanoparticles through the intranasal route. By applying adhesive components such as chitosan to nanoparticles, we can improve the drug internalization of olfactory neurons, increasing bioavailability. The molecule size and surface properties of nanoparticles can be accommodated to adjust to both passive and active drug targeting, which might be helpful in drug administration. Additionally, nanoparticles protect drugs from degradation, improving stability and delivery efficacy (Chenthamara et al., 2019). 

In the study of (Wang et al., 2025), the authors designed and synthesized ionizable lipids. Specifically, small-molecule ligands known to traverse the BBB, such as MK-0752, were chemically coupled with amino lipids to synthesize a series of structurally diverse BBB-crossing lipids. The BBB-crossing module enables the nanoparticle to cross the BBB. The amino groups function to provide ionization properties, enabling the lipids to exhibit variable charge states, determining their apparent pKa, a critical parameter and the basis of endosomal escape. The lipid tails form the hydrophobic core of the nanoparticle, the length of which influences the efficiency of MK-series BLNPs in delivering mRNA to the brain. The study administered the drug intravenously into mice. MK16 BLNPs are distributed throughout the body, with most of the dose being absorbed by the liver and part of the dose (15.3±0.4%) in the brain. Notably, the study also demonstrated that caveolae and γ-secretase might be critical mediators in facilitating the BBB crossing of MK16 BLNPs (Wang et al., 2025). The study proved that lipid nanoparticles are capable of carrying large organic particles like mRNA, providing a theoretical possibility for delivering paroxetine and JDTic. However, it also showed a high rate of missing the targeted administration region, which could cause systemic side effects or increased metabolic stress. In order to target the brain better, we referred to an alternate model of LNP. In “Dopamine-loaded lipid-based nanocarriers for intranasal administration of the neurotransmitter: A comparative study”, the researchers structured the SLN based on the self-emulsifying lipid Gelucire® 50/13, coated with stearoyl polyoxyglycerides, surrounded by a hydrophilic polyoxyethylene chain shell. The study evaluated two types of liposomes, which were composed of an aqueous drug solution core and the coating fat phase, which was made of a mixture of phosphatidyl choline, phosphatidyl glycerol, and cholesterol. Lip 1 was uncoated, while Lip 2 was coated with Chitosan-glutathione conjugate. Both liposomes were outperformed by SLNs in encapsulation efficiency. The two types of SLNs are unmodified DA-SLN (SLN 1) and Glycol Chitosan-associated GCS-DA-SLN (SLN 2). In the case of SLN 2, the GCS component contributed to the network on the shell of the nanoparticle, reducing the leakage of the drug. Therefore, SLN 2 outperformed SLN 1 in encapsulation efficiency. The drug was administered intranasally. The GCS component increased the mucoadhesive ability of SLN 2, allowing the nanoparticles to be taken up with high efficiency by olfactory ensheathing cells (OECs), enabling better drug administration. The study also proved that the SLNs lack cytotoxicity towards OECs, rendering it a rather safe route (Trapani, A et al., 2021). 

Inspired by SLN 2, the general image of our proposed lipid nanoparticle carrier of paroxetine is shown Figure 1. We surrounded the lipid basis and its stearoyl polyoxyglycerides shell with a hydrophilic layer and GCS in order to increase the mucoadhesive ability of the nanoparticle. Notably, according to the structure of paroxetine, it will be involved in the outer network of hydrogen bonds and molecular interactions, as dopamine was in the paper. The methods of preparation were recorded in the reference (Trapani, A et al., 2021). We are uncertain if chemicals like Gelucire® 50/13 or stearoyl polyoxyglycerides still apply here. Specific components of the designed SLN need to be determined in further research. 

JDTic does not display good lipophilic properties. To avoid the challenge of encapsulation of hydrophilic compounds in SLN, as mentioned in the paper, since the paper suggests that liposomes have aqueous cores (Trapani, A et al., 2021), we propose to use a liposome carrier to deliver JDTic, as shown in Figure 2. Notably, although in the study of Wang et al., the delivered mRNA is aqueous, the following studies and property determination are all done in the context of intravenous delivery. We are not sure if the results still apply to intranasal administration. Thus, we did not adopt the LNP used in this study (Wang et al., 2025). We propose to use the same component as coating lipids as used in the reference. To increase encapsulation efficiency, an appropriate polymer coating (e.g., chitosan, alginate) may be applied to limit such drug leakage. Its preparation methods were also recorded (Trapani, A et al., 2021). Still, the exact component of the liposome requires further determination. 

5. Nasal Route

After intranasal administration, drugs primarily enter the brain by interacting with neural pathways within the nasal cavity. Specifically, drugs absorbed from the nasal mucosa can be transported along the axons of the olfactory and trigeminal nerves. Olfactory sensory neurons take up the drugs and transport them via their axons to the olfactory bulb, the first site of entry into the brain. Subsequently, drugs can diffuse further from the olfactory bulb to more distant brain regions, such as entering cortical and hippocampal areas via cerebrospinal fluid circulation. Beyond intracellular transport along nerve axons, drugs may also enter through extracellular pathways—specifically, by crossing tight junctions between epithelial cells into the lamina propria of the submucosal layer, then traversing perineural spaces to ultimately reach the subarachnoid space, thereby diffusing into brain tissue (Erdő et al., 2018). 

The primary advantage of the intranasal route of administration lies in its ability to bypass the blood-brain barrier, enabling direct delivery of drugs to the central nervous system. This opens therapeutic possibilities for large molecules or hydrophilic drugs—such as dopamine, neuropeptides, and even mRNA—that struggle to cross the BBB. Compared to oral or intravenous administration, this route typically yields higher brain bioavailability, achieving greater brain tissue exposure at equivalent doses. Simultaneously, reduced systemic circulation helps minimize peripheral side effects. Furthermore, intranasal administration offers non-invasive delivery, facilitates patient self-administration, and provides a relatively rapid onset of action. It demonstrates potential for treating both acute and chronic central nervous system disorders, including neurodegenerative diseases, epilepsy, and pain management (Erdő et al., 2018). 

6. Developments and Limits

JDTic has yet to be applied clinically, and its effectiveness in humans is still lacking validation. Also, existing study suggests that nonsustained ventricular tachycardia is a potential JDTic toxicity in humans (Buda et al., 2015), indicating potential medical safety problems. Further assessments and studies on the drug safety of JDTic are required. 

The reported effectiveness of the drugs on dissociation is conflicting, and any significantly effective drug for dissociative symptoms is not clear yet. For instance, although opioid receptor antagonists are believed to be effective in dissociation, research indicates that naltrexone, an opioid receptor antagonist, cannot cancel out the dissociative symptoms induced by ketamine (Jacobson et al., 2020). It is possible that ketamine induced dissociation is not the same as dissociation observed in DID patients in terms of mechanisms. However, further determination is still needed.

The stability and storage of lipid nanoparticles still need to be improved. The paper suggests that the liposome can be stored for 6 days under 4 degrees Celsius, while SLN can maintain stability for 1 month before undergoing particle aggregation and drug autoxidation. Also, the encapsulation efficiency of liposomes is not quite satisfying due to drug leakage, and the polymer coating can only improve this condition to a limited extent (Trapani, A et al., 2021). The refrigeration requirement might lead to increased storage and transportation costs, and the drug delivery efficacy requires further improvement. 

Due to the omnipresence of the serotonin receptors and KORs in the brain, we are not sure if the impact of the medication on the whole brain will bring any side effects. Medication safety requires future confirmation. 

As this study is about mental illness medication, which must be applied carefully, this study lacks experimental data, and the effectiveness of the therapeutics proposed in this study remains to be seen. Further experiment is needed to test its viability, and more assessments of its effectiveness are required.

The glutamatergic system might also be related to the dissociative symptoms of DID. Glutamate receptor can be classified into ionotropic glutamate receptors(iGluRs), which are ion channels, and metabotropic glutamate receptors (mGluRs), which are GPCRs. They are widely distributed in the central nervous system (CNS). They are involved in synaptic transmission and regulate learning, memory, and neural plasticity through long-term potentiation (LTP) and long-term depression (LTD) (Wang et al., 2024). Ketamine is a dissociogenic drug that influences NMDA, a kind of iGluR. Moreover, glutamate levels in the anterior cingulate cortex positively correlated with dissociative symptoms in a borderline personality disorder sample. However, evidences are still limited, and the medications acting on the glutamatergic system show conflicting results on relieving dissociative symptoms (Purcell et al., 2024). Therefore, we did not concentrate on this neurotransmitter system. However, we believe there might be a potential relationship between the glutamatergic system and the dissociation, which calls for further study. 

Clinical evidence suggests that DID is induced by childhood abuse (Purcell et al., 2024). It has been suggested that epigenetics is the link between environmental factors and physiological features (Weir, 2012), so we are convinced that DID can also be related to epigenetics, which may inspire further exploration or other treatment routes. Additionally, DID was also proven to display multiple neural structural differences compared to normal brains, such as reduced cortical and subcortical volumes in the hippocampus, amygdala, and parietal structures (Blihar et al., 2020), or dysregulation of activity in the prefrontal cortex, amygdala, and other brain areas (Shimiaie, 2025). While this paper mainly focused on the neurochemical basis of DID, this might suggest another perspective on the neurological basis of the disorder, thus leading to future research. 

In DID, the dissociation symptoms usually appear along with other disorders, namely depression, anxiety, and somatization, which could require concomitant drug application (Purcell et al., 2024). To explore drug interactions and avoid adverse effects due to concomitant drugs, an artificial intelligence application has been introduced, and a systematic review of the viability of this method has been conducted (Zhang et al., 2024). With further development, this application of AI could lead to more improvement in DID treatment. 

The treatment mentioned in this paper may also be applicable to dissociation under other circumstances. However, further research is needed to validate this hypothesis, since dissociative symptoms could appear slightly differently in different illnesses.

Considering nasal administration, there could be ways to improve the drug delivery efficiency. The nasal epithelium can be a rate-limiting barrier of drug uptake, where cells are joined together by tight junctions. Therefore, permeation enhancers, such as borneol, chitosan, and cyclodextrins, are applied to enhance drug transportation. The effectiveness of intranasal administration is more influenced by the administration technique compared to other routes. The administration technique should be efficient and feasible for the patient to administer by themselves. Nasal drops spread over a larger area than nasal sprays and display a higher deposition rate compared to nasal sprays, if administered correctly. While drops are more easily cleared from the administration region than sprays, adding mucoadhesive agents can address this problem. However, nasal drops require a highly accurate administration technique and correct head position. Some novel intranasal delivery devices include the Vianase^TM electronic atomizer and the bi-directional delivery device Opt-Powder by Optinose^®, the potential of which on lipid nanoparticle delivery requires further studies. Multiple approaches have been studied to increase brain uptake of drugs, including increasing drug lipophilicity, increasing carrier-mediated transport through the BBB, and decreasing efflux by applying transport inhibitors (Erdő et al., 2018). Studies of delivery efficacy-enhancing methods could further propel the development of intranasally administered mental disorder medications.

7. Conclusion

This paper offers a novel insight into DID medical treatment based on KOR and serotonergic system and LNP delivery through the intranasal route. Although this treatment possesses the theoretical advantage of targeting the brain and improving bioavailability, its clinical transformation still needs to overcome major obstacles. JDTic, a proposed medication, has not been put into clinical application and faces safety challenges. The stability of nanoparticle carriers could be improved. There is a lack of experimental data. Future studies could focus on medication trials, nanoparticle carrier improvement, delivery efficacy enhancers, and more exploration into the neurologic basis of DID. We hope to develop safe and accurate medical therapy for DID. 

References

Benedetti, M. S., Whomsley, R., Poggesi, I., Cawello, W., Mathy, F.-X., Delporte, M.-L., Papeleu, P., & Watelet, J.-B. (2009). Drug metabolism and pharmacokinetics. Drug Metabolism Reviews, 41(3), 344–390. https://doi.org/10.1080/10837450902891295

Blihar, D., Delgado, E., Buryak, M., Gonzalez, M., & Waechter, R. (2020). A systematic review of the neuroanatomy of dissociative identity disorder. European Journal of Trauma & Dissociation, 4(3), 100148. https://doi.org/10.1016/j.ejtd.2020.100148

Buda, J., Carroll, F., Kosten, T. et al. A Double-Blind, Placebo-Controlled Trial to Evaluate the Safety, Tolerability, and Pharmacokinetics of Single, Escalating Oral Doses of JDTic. Neuropsychopharmacol 40, 2059–2065 (2015). https://doi.org/10.1038/npp.2015.27

Chenthamara, D., Subramaniam, S., Ramakrishnan, S. G., Krishnaswamy, S., Essa, M. M., Lin, F.-H., & Qoronfleh, M. W. (2019). Therapeutic efficacy of nanoparticles and routes of administration. Biomaterials Research, 23(1), 20. https://doi.org/10.1186/s40824-019-0166-x

Erdő, F., Bors, L. A., Farkas, D., Bajza, Á., & Gizurarson, S. (2018). Evaluation of intranasal delivery route of drug administration for brain targeting. Brain Research Bulletin, 143, 155–170. https://doi.org/10.1016/j.brainresbull.2018.10.009

Jacobson, M. L., Browne, C. A., & Lucki, I. (2020). Kappa opioid receptor antagonists as potential therapeutics for stress-related disorders. Annual Review of Pharmacology and Toxicology, 60, 615–636. https://doi.org/10.1146/annurev-pharmtox-010919-023317

Kitamura, S., Yasuno, F., Inoue, M., Kosaka, J., Kiuchi, K., Matsuoka, K., Kishimoto, T., & Suhara, T. (2014). Increased binding of 5-HT1A receptors in a dissociative amnesic patient after the recovery process. Psychiatry Research: Neuroimaging, 224(1), 67–71. https://doi.org/10.1016/j.pscychresns.2014.07.001

Kowalska, M., Nowaczyk, J., Fijałkowski, Ł., & Nowaczyk, A. (2021). Paroxetine—Overview of the molecular mechanisms of action. International Journal of Molecular Sciences, 22(4), 1662. https://doi.org/10.3390/ijms22041662

Marshall, R. D., Lewis-Fernandez, R., Blanco, C., Simpson, H. B., Lin, S.-H., Vermes, D., Garcia, W., Schneier, F., Neria, Y., Sanchez-Lacay, A., & Liebowitz, M. R. (2007). A controlled trial of paroxetine for chronic PTSD, dissociation, and interpersonal problems in mostly minority adults. Depression and Anxiety, 24(2), 77–84. https://doi.org/10.1002/da.20176

Munro, T. A., Berry, L. M., Van’t Veer, A., Béguin, C., Carroll, F. I., Zhao, Z., Carlezon, W. A., & Cohen, B. M. (2012). Long-acting κ opioid antagonists nor-BNI, GNTI and JDTic: Pharmacokinetics in mice and lipophilicity. BMC Pharmacology, 12(1), 5. https://doi.org/10.1186/1471-2210-12-5

Purcell, J. B., Brand, B., Browne, H. A., Chefetz, R. A., Shanahan, M., Bair, Z. A., Baranowski, K. A., Davis, V., Mangones, P., Modell, R. L., Palermo, C. A., Robertson, E. C., Robinson, M. A., Ward, L., Winternitz, S., Kaufman, M. L., & Lebois, L. A. M. (2024). Treatment of dissociative identity disorder: Leveraging neurobiology to optimize success. Expert Review of Neurotherapeutics, 24(3), 273–289. https://doi.org/10.1080/14737175.2024.2316153

Pytliak, M., Vargová, V., Mechírová, V., & Felšöci, M. (2011). Serotonin receptors – From molecular biology to clinical applications. Physiological Research, 15–25. https://doi.org/10.33549/physiolres.931903

Reeves, K. C., Shah, N., Muñoz, B., & Atwood, B. K. (2022). Opioid receptor-mediated regulation of neurotransmission in the brain. Frontiers in Molecular Neuroscience, 15, 919773. https://doi.org/10.3389/fnmol.2022.919773

Roth, B. L., Baner, K., Westkaemper, R., Siebert, D., Rice, K. C., Steinberg, S., Ernsberger, P., & Rothman, R. B. (2002). Salvinorin A: A potent naturally occurring nonnitrogenous κ opioid selective agonist. Proceedings of the National Academy of Sciences, 99(18), 11934–11939. https://doi.org/10.1073/pnas.182234399

Shimiaie, J. (2025, January 26). What happens in the brain in dissociative identity disorder? Psychology Today. https://www.psychologytoday.com/gb/blog/an-interpersonal-lens/202501/what-happens-in-the-brain-in-dissociative-identity-disorder

Simeon, D., Hollander, E., Stein, D. J., DeCaria, C., Cohen, L. J., Saoud, J. B., Islam, N., & Hwang, M. (1995). Induction of depersonalization by the serotonin agonist meta-chlorophenylpiperazine. Psychiatry Research, 58(2), 161–164. https://doi.org/10.1016/0165-1781(95)02538-8

Thomas, J. B., Atkinson, R. N., Vinson, N. A., Catanzaro, J. L., Perretta, C. L., Fix, S. E., Mascarella, S. W., Rothman, R. B., Xu, H., Dersch, C. M., Cantrell, B. E., Zimmerman, D. M., & Carroll, F. I. (2003). Identification of (3R)-7-hydroxy-N-((1S)-1-{[(3R,4R)-4-(3-hydroxyphenyl)-3,4-dimethyl-1-piperidinyl]methyl}-2-methylpropyl)-1,2,3,4-tetrahydro-3-isoquinolinecarboxamide as a novel potent and selective opioid κ receptor antagonist. Journal of Medicinal Chemistry, 46(14), 3127–3137. https://doi.org/10.1021/jm030094y

Trapani, A., De Giglio, E., Cometa, S., Bonifacio, M. A., Dazzi, L., Di Gioia, S., Hossain, M. N., Pellitteri, R., Antimisiaris, S. G., & Conese, M. (2021). Dopamine-loaded lipid based nanocarriers for intranasal administration of the neurotransmitter: A comparative study. European Journal of Pharmaceutics and Biopharmaceutics, 167, 189–200. https://doi.org/10.1016/j.ejpb.2021.07.015

Walsh, S. L., Strain, E. C., Abreu, M. E., & Bigelow, G. E. (2001). Enadoline, a selective kappa opioid agonist: Comparison with butorphanol and hydromorphone in humans. Psychopharmacology, 157(2), 151–162. https://doi.org/10.1007/s002130100788

Wang, C., Xue, Y., Markovic, T., Li, H., Wang, S., Zhong, Y., Du, S., Zhang, Y., Hou, X., Yu, Y., Liu, Z., Tian, M., Kang, D. D., Wang, L., Guo, K., Cao, D., Yan, J., Deng, B., McComb, D. W., … Dong, Y. (2025). Blood–brain-barrier-crossing lipid nanoparticles for mRNA delivery to the central nervous system. Nature Materials. https://doi.org/10.1038/s41563-024-02114-5

Wang, J., Liu, A. G., Ma, Z. B., Jia, J., Zhang, Q., & Yan, X. K. (2024). 谷氨酸受体介导的中枢神经突触可塑性改变及针刺调节机制研究进展 [Research progress on glutamate receptor-mediated synaptic plasticity changes in the central nervous system and acupuncture regulation mechanism]. World Science and Technology, 26.

Weir, K. (2012, June). The roots of mental illness. Monitor on Psychology, 43(6), 30. https://www.apa.org/monitor/2012/06/roots

Zhang, Y., Deng, Z., Xu, X., Feng, Y., & Junliang, S. (2024). Application of artificial intelligence in drug–drug interactions prediction: A review. Journal of Chemical Information and Modeling, 64(7), 2158–2173. https://doi.org/10.1021/acs.jcim.3c00582

About the author

Kaifeng Zhu

Kaifeng is currently an 11th grade student in EHSBNU, graduating in 2027, and anticipating future study in biomedicine.

The post Possible Lipid Nanoparticle Drug Treatment for DID Based on its Biological Mechanism Administered from the Nasal Route appeared first on Exploratio Journal.

I. Abstract

Imagine a universe where nothing has a definite state until you look at it. The tension between scientific abstraction and the real human experience has elevated with the emergence of quantum physics, a field that reveals a nature of reality that subverts the “common sense” world we perceive. Unlike human experience, grounded in concrete, sequential events, quantum physics suggests a probabilistic, interconnected universe where particles exist in multiple states until observed. This abstract scientific worldview challenges how humans perceive reality and raise questions about whether quantum physics, and scientific frameworks in general, can encapsulate individual’s lived human experience. Amidst this ongoing debate that dates to the 1920s, when quantum physics theories were first proposed by Max Planck, two thinkers across decades offer two competing views. Kurt Riezler, in 1940, critiques quantum physics’ inability to capture lived reality through the psi function’s probabilistic vagueness, the anonymous observer’s displacement of subjectivity, and the Aristotelian call for science rooted in reality. Conversely, Carlo Rovelli, in the 2010s, defends quantum physics through relational ontology, framing its uncertainty as a gateway for imagination and a sign of the universe’s interconnectedness. This paper argues that Rovelli’s interpretation is philosophically rich yet still fails to bridge quantum physics to individual human existence, which was Riezler’s main concern. Despite holding different stances, both thinkers value wonder, humility, and humanity in scientific inquiry and affirms the paper’s broader implication that science and philosophy must work together to reveal universal truths. 

Keywords: Quantum Physics, Psi Function (ψ), Anonymous Observer, Relational Ontology

II. Introduction

The tension between science and philosophy has long centered on the relationship between scientific models and humanity, the lived human experience. This paradox became especially relevant with the rise of quantum physics, which redefined humans’ knowledge of causality and relations. In the early twentieth century, German philosopher and poet Kurt Riezler warned that modern science had grown estranged from its human roots by reducing the universe to probabilities and formulas detached from meaning and purpose and so had quantum physics. On the other hand, contemporary physicist-philosopher Carlo Rovelli embraces the uncertainty of quantum physics, presenting it not as a barrier to human understanding but as an invitation for people to rethink what reality actually is.

This paper argues that Riezler’s Aristotelian standpoint critiques the non-teleological (teleological is a philosophical term denoting the purpose something serves in a material world) nature of quantum physics, its inaccuracy, and its lack of human participation. On the other hand, Rovelli supports quantum physics, believing that its uncertainty philosophically reveals a world woven from interactions. However, I argue that Rovelli’s interpretation does not entirely resolve Riezler’s concern, despite being philosophical and purposeful, as it still fails to resolve the problem of whether quantum physics is linked to everyday individual existence.

Both Rovelli and Riezler share a conviction, rare in scientific discourse, that the pursuit of knowledge is inseparable from the pursuit of happiness. However, their perceptions of happiness diverge: for Riezler, serenity arises from a teleological account of nature grounded in lived experience; for Rovelli, happiness stems from the realization of individuals’ interconnectedness with an indeterminate, relational universe. 

III. Riezler’s Critique of Quantum Physics

1. Probability and the Psi Function (ψ)

Kurt Riezler’s critique of quantum physics stems from its disconnection from human experience and from the universe’s complexity. He argues that scientific equations and probabilities inaccurately account for the human world. He specifically refers to the psi function ψ. In the physics context, the psi function is not the derivative of the logarithm of the gamma function in math, but a wave function that describes a state of a quantum system or a particle. It is used to calculate the probability density of finding a particle with a certain quality or in a particular location (OpenStax, n.d). This wave is something unclear, since, according to Schrodinger’s formula, it evolves unless observed by someone.

First, Riezler explained that the psi function’s probabilistic framework of quantum theory is vague and inaccurate. The psi function does not calculate each event individually but as a wave of probabilities and potential outcomes of the event. “You repeat the same experiment as often as possible,” Riezler observes. “The outcome is a catalogue of various reactions.” (Riezler, 1940, p. [29]). In other words, the experiment does not show what one phenomenon is; it only shows the probabilities of the different outcomes that appeared of that phenomenon. The knowledge thus gained, he writes, is “knowledge about the class to which this element belongs,” not about the element itself (Riezler, 1940, p. [30]). The psi function’s probabilities may describe how often certain results occur, but they cannot tell us the specific implications of each result. 

Moreover, Riezler argues that the psi function oversimplifies and distorts reality’s complexity. “The psi function of quantum theory,” he writes, “base the large world on the small… Thus your science is a mirror inadequate to the object to be reflected” (Riezler, 1940, p. [27-28]). He argues that, rather than deriving its concepts from direct experience of the macroscopic world, quantum physics attempts to build that world out of abstract, artificial tools of the microscopic. The “small” world of particles, which is accessible only through indirect measurement and symbolic modeling, becomes the foundation for explaining the “large” reality. The phrase “base the large world on the small” summarizes the metaphysical absurdity (‘atopan’) Riezler detects in modern science (Riezler, 1940, p. 28). He argues that the microphysical cannot measure the macro world, just as the visible cosmos cannot be explained through invisible constructs. This inversion, for Riezler, is not only epistemological (relating to the theory of knowledge concerning its methods, validity, and scope) but existential: people now seek to investigate the visible through the invisible, the concrete through the hypothetical. 

2. The Anonymous Observer and the Displacement of Subjectivity

Linked to the psi function is Riezler’s notion of the anonymous observer. The “observer” in quantum physics is not a real being with emotions, memory, or moral judgment, but a neutral apparatus. For Riezler, the lack of a conscious mind that performs the measurement is flawed: it assumes that objectivity can exist independently of the subject. But in truth, he argues, the subjective is actually the foundation of the objective in a human-centered world. This inversion also aligns with the etymology of the two words. Subjective comes from the Latin “subicere”—meaning “to throw under,” to lay the foundation upon which one stands—while objective derives from “obicere”––meaning “to throw before,” something which is set out in front of the subjective. The subject, consciousness, is thus the ground, the underlying presence that makes any measured object real. Riezler argues that it is inaccurate to pursue objective knowledge through an “anonymous observer” that lacks a mind since observation, by its nature, implies a standpoint, and standpoints equate subjectivity.

3. Connecting Riezler’s Argument to Ancient Philosophers

Riezler upholds the Aristotelian view of science as an inquiry, a living path that connects natural science, physics, math, ethics, and human beings. According to Schulman Adam Leonin, his essay “Quantum and Aristotelian Physics,” Aristotle’s methodos refers to the “search for knowledge itself, rather than to a set of rules governing the research. Sometimes [Aristotle] speaks not of methodos but simply of hodos, that is, a path or way… Aristotle is always conscious of the danger of too quickly fastening upon technical terms that either fail to capture the phenomena fully or that cover over a problem that deserves further attention. The path to knowledge should repeatedly return to surface impressions to verify that the precision of our principles has not been won at the price of narrowing and distorting our vision” (Schulman, 1989, pp. 9-10). Riezler shares this caution, asserting that inquiry should always link back to lived experience. This verifies that science’s conceptual frameworks do not flatten and distort the way reality functions on an everyday scale. 

Riezler’s critique echoes Aristotle’s notion of theoria (the activity of contemplation as the highest human act) and his own belief in humans’ fundamental desire for knowledge. That is, if people cease to investigate reality by themselves and instead rely on external tools to do so, they diminish their inherent desire for active contemplation. This perspective subtly alludes to Plato’s critique of writing in Phaedrus. Plato argues that writing is an elixir of forgetfulness for the souls that rely on it. This invention strips humans of their active recollection and contemplations as they rely on these external symbols to remember. These ancient philosophers, Aristotle and Plato, were all concerned about the danger of these external tools, whether it is writing or science. 

IV. Rovelli’s Relational Ontology of Quantum Physics and Its Philosophical Implications

Having established Riezler’s concerns about quantum physics’ disconnection from human experience, we now turn to how Rovelli transforms these same uncertainties into philosophical opportunities. Carlo Rovelli’s interpretation of quantum physics begins from an acceptance of uncertainty as an essential feature of the universe, which he perceives as fundamentally relational, not absolute. The term, relational ontology, refers to his view that relations between entities are more important than the identities of the entities. More specifically, Rovelli insists that the foundations of modern physics stemmed not from rigid formulas but from imagination and philosophical vision, the very qualities Riezler championed as meaningful science grounded in human experience. In Reality Is Not What It Seems: The Journey to Quantum Gravity, he asserts that Einstein developed relativity not from equations but from mental images of the universe: “the equations, for him, came afterwards; they were the language with which to make concrete his visions of reality… the theory of general relativity is not a collection of equations: it is a mental image of the world arduously translated into equations” (Rovelli et al., 2018, p. [76]). In other words, Einstein’s insights arose not from mathematical manipulations but from a poetic act of visualization of the universe as a unified fabric of space and time. Through this lens, physics becomes a philosophical, and even aesthetic, endeavor that translates intuition into symbols.

This perspective reverses Riezler’s critique of quantum physics as an abstract catalogue of aggregates detached from lived experience. While Riezler feared that equations stripped humanity, Rovelli views them as a medium of humane imagination. Rovelli finds in quantum physics a form of Romanticism, a reverence for the unseen harmony binding all matters together. In the opening chapter of Reality is Not What it Seems, Rovelli praised Lucretius’ poem “De  Rerum Natura” (“On the Nature of The Universe”)––quoting “we are all sprung from heavenly seed…”––which, in his words, “expresses in luminous verse philosophical questions, scientific ideas, refined arguments” all at once” (Rovelli et al., 2018, p. [20]). He argued that “the beauty of the poem lies in the sense of wonder which pervades the vast atomic vision –– the sense of the profound unity of things, derived from the knowledge that we are all made of the same substance as are the stars, and the sea” (Rovelli et al., 2018, p. [21]). By tracing modern science to ancient philosophical insights of the universe, Rovelli demonstrates how quantum physics, far from being only a statistical tool, is a philosophical exploration of the universe’s interconnectivity.

Paul Dirac’s principle of superposition illustrates the interconnectedness of imagination and precision. According to Dirac, a quantum entity such as a photon exists in multiple possible states simultaneously until measured. The double-slit experiment, which demonstrates that photons and electrons behave as both waves and particles, exemplifies this insight. When photons or electrons pass through two slits unobserved, they produce an interference pattern, behaving as waves distributed across space. Yet, when one just looks to see or anticipates which slit they pass through, the interference vanishes; the pattern collapses into two discrete bands. This wave-particle duality overthrows our understanding of the traditional wave function and Riezler’s argument about the anonymous observer. Here, the very act of observation transforms what is observed. 

Another experiment that addresses the inseparable relationship between the observed and the observer is Schrödinger’s cat (1935). The experiment involves a cat sealed in a box with a radioactive atom, a Geiger counter, a hammer, and poison. The atom’s decay is governed by quantum probability (50% chance of decay): it may or may not release radiation that would kill the cat in a given time frame. The cat is neither definitively alive nor dead, suspended in a superposition of both possibilities, until an observer opens the box. This experiment shows that quantum states are undetermined until observed. As Rovelli explains in Helgoland, “facts that are real with respect to an object are not necessarily so with respect to another” (Rovelli et al., 2022, p. [72]). The radiation emitted by the atom, as Rovelli emphasizes, does not have a definite value until it affects another system. The fate of the cat is indeterminate until relations between the atom, the cat, and the observer are established. In this framework, reality emerged only through interactions. 

As the psychologist Amos Tversky puts it, “reality is a cloud of possibility, not a point” (Stockton, 2017). The analogy of reality to misty clouds in a blurred photograph captures the ambiguity of this relational world: when an image appears unclear, one may ask whether the blur arises from the photographer’s unsteady hands or from the mist itself. For Rovelli, this distinction collapses as the uncertainty belongs to the act of seeing as much as to the seen. Reality’s imperfection is an intrinsic quality of existence.

The indeterminacy of all things in the absence of relational context challenged earlier philosophers and scientists, such as Newton and Hobbes. They envisioned a universe governed by immutable laws. They sought to dispel the “clouds” since truth resided in the elimination of ambiguity. Rovelli’s argument of quantum physics, however, weaves the uncertainty as an essential part of truth. Thus, Rovelli’s quantum mechanical worldview dissolves the Cartesian boundary between subject and object, suggesting instead a universe intertwined with relations.

In psychological terms, this relational worldview connects to human serenity. For Rovelli, serenity arises not from mastering the world but from recognizing one’s belonging within an interdependent universe and one’s ignorance amidst its complexity. This feeling of serenity, which stems from recognition of one’s ignorance, aligns with ancient philosophers such as Socrates and Confucianism. In Plato’s Apology, Plato wrote Socrates’ assertion that “I am wisest of all the Greeks because that which I do not know, I do not think I know either” (Plato, n.d., p. 83). Therefore, to live, as Rovelli suggests, is to dwell within the cloud of possibilities and to accept the world not as a set of certainties but as a field of relations continuously unfolding.

In the closing pages of Helgoland, Rovelli turns to Shakespeare’s The Tempest, quoting Prospero’s famous farewell: 

“These are actors,

As I foretold you, were all spirits and

Are melted into air, into thin air:

And, like the baseless fabric of this vision…

Yea, all which it inherit, shall dissolve.

And like this insubstantial pageant faded,

Leave not a rack behind. We are such stuff

As dreams are made on, and our little life 

Is rounded with sleep.”

The quotation encapsulates Rovelli’s vision of reality as transient, woven of relations that shimmer briefly before dissolving. The last sentence echoes Rovelli’s belief in “confirmed hallucination.” This concept echoes 19th-century French philosopher Hippolyte Taine’s insight that “external perception is an internal dream which proves to be in harmony with external things.” Like the character Prospero’s vision of life as a dream sustained by momentary harmony, Rovelli’s universe is a network of fleeting interactions whose beauty lies in their impermanence. 

However, even Rovelli does not resolve Riezler’s question about quantum physics’ inability to capture the full depths and dimensions of the universe, which, I believe, is incapable to be explained even by modern philosophy and technology. It requires the ongoing, collaborative research of both philosophy and science, fields that are deeply connected.

V. Conclusion

In the end, Rovelli concedes that the reach of quantum physics is not unlimited. He fails to see any quantum explanation for subjectivity, perceptions, intelligence, consciousness, or any other aspects of our mental life. Quantum phenomena intervene in the dynamics of atoms, photons, electromagnetic impulses, and all other microscopic structures that give rise to our body, but there is nothing specifically quantum that could help us understand what thoughts, perception, and subjectivity are. Even in a neuroscience context, neurons and their signaling molecules are too large for quantum phenomena to play a role in their functioning, as expressed by Daniel Demmet. He stated, “Most biologists think that quantum effects all just cancel out in the brain, that there’s no reason to think they’re harnessed in any way. Of course they’re there; quantum effects are there in your car, your watch, and your computer. But most things — most macroscopic objects — are, as it were, oblivious to quantum effects.” (Penrose and Dennett, 1995). This acknowledgement is not a defeat, but a recognition that even the most sophisticated physics does not unravel the mystery of consciousness. 

Riezler would have regarded this concession as proof that the essence of human existence, with its moral, existential dimensions, lies beyond the restriction of theoretical science. But Rovelli views this limitation as a form of serenity. For him, the inability of quantum physics to explain human experience does not diminish its depth. Nevertheless, the distance between Riezler and Rovelli may not be as great as it first appears. Both reject the illusion of absolute mastery of the universe and support an ideal form of science rooted in wonder, humility, and humanity. To me, quantum physics does not need to fully explain the universe and our consciousness to be valuable. 

VI. References

Jedlicka P. (2017). Revisiting the Quantum Brain Hypothesis: Toward Quantum (Neuro)biology? Frontiers in molecular neuroscience, 10, 366. https://doi.org/10.3389/fnmol.2017.00366

Lewis, M. (2017). The Undoing Project: A Friendship that Changed our Minds. W.W. Norton & Company.

OpenStax (Ed.). (n.d.). 7.2: Wave Functions. LibreTexts Physics. https://phys.libretexts.org/Bookshelves/University_Physics/University_Physics_(OpenStax)/
University_Physics_III_Optics_and_Modern_Physics_(OpenStax)/07%3A_Quantum_Mechanics/7.02%3A_Wavefunctions

Plato. (n.d.). Plato, Euthyphro. Apology. Crito. Phaedo: Apology (H. N. Fowler, Trans.). Loeb Classical Library.

Riezler, K. (1940). Physics and Reality: Lectures of Aristotle on Modern Physics. Yale University Press.

Rovelli, C., Carnell, S., & Segre, E. (2018). Reality is not What it Seems: the Journey to Quantum Gravity. Riverhead Books.

Rovelli, C., Segre, E., & Carnell, S. (2022). Helgoland: making sense of the quantum revolution. Riverhead Books.

Schulman, A. L. (1989). Quantum and Aristotelian Physics. Harvard University ProQuest Dissertations & Theses.

Stockton, S. S. (Ed.). (2017, September 9). Living in a Cloud of Possibilities. Retrieved November 25, 2025, from https://intrinsicinvesting.com/2017/09/29/living-cloud-possibilities/

About the author

Joanna Zhang

Joanna Zhang is currently a junior at Milton Academy, with academic and research interests that include philosophy, quantum physics, religious studies, classics, and Russian literature.

Outside academics, Joanna is a passionate creative writer, winning two Massachusetts region gold keys in poetry in the Scholastic Arts and Writing Award and publishing her novella, Caroline, under Archway Simon and Schuster. She also loves dancing, specifically hip-hop and K-pop, and choreographing.

The post The Human Element: Riezler’s Critique and Rovelli’s Defense of Quantum Physics appeared first on Exploratio Journal.

Abstract

The field of bionic limb technology is currently undergoing a pivotal paradigm shift, transitioning from purely functional robotic design to highly integrated neuroprosthetic systems. While contemporary advancements in neural interfaces and powered robotics have improved user capabilities, clinical translation remains hampered by issues such as signal instability, limited sensory feedback, and poor biocompatibility of interfaces. This literature review synthesizes recent progress in the clinical translation of bionic limbs, focusing on three core pillars: advanced neural interfaces, osseointegration, and patient-centric design. We explore the role of bidirectional control, the application of reinforcement learning for robust intent decoding, and the integration of digital twins for personalised residuum management. By evaluating the co-evolution of surgical innovation and robotic hardware, this review highlights the critical need for a “clinical-push” methodology, in which design is driven by long-term residuum health rather than mere functional performance. The findings emphasise that successful clinical outcomes depend on treating the prosthetic and the user’s altered physiology as a single, integrated system, ultimately identifying key barriers to translation and proposing a framework for more equitable, accessible, and durable prosthetic care. 

Keywords: Neuroprosthesis, Bionic Limbs, Neural Interfaces, Osseointegration, Rehabilitation, Neuroplasticity, Bidirectional, Targetted Muscle Reinnervation (TMR), and Agonist-Antagonist Myoneural Interface (AMI)

1. Introduction: 

The cinematic image of a sophisticated, seamlessly integrated artificial limb, once a domain of science fiction, is slowly becoming a clinical reality. For centuries, the ambition to replace missing limbs with functional, anthropomorphic counterparts has driven immense innovation. Yet, the reality of many amputees remains defined by the limitations of traditional, socket-based prostheses. While these conventional devices provide basic mobility, they are frequently associated with chronic pain, skin breakdown, and osseous degeneration, leading to high rates of device abandonment. The core of this challenge lies in the “HMI paradox” whereby, as the level of amputation increases, the technical complexity required for control increases as well, while the available biological signals from the residual limb diminish. 

To overcome these barriers, the field has increasingly turned towards bionic limbs, which aim to replicate biological function through a marriage of robotics, surgery, and neuroscience. Unlike passive devices, modern bionic limbs leverage sophisticated neural interfaces, such as Targeted Muscle Reinnervation (TMR) and the Agonist-Antagonist Myoneural Interface (AMI), to create direct channels for motor intent and sensory feedback. Furthermore, the emergence of osseointegration, where prosthetics are directly skeletally attached, offers a stable, reliable foundation that bypasses the limitation of soft-tissue socket interfaces entirely. 

However, technology alone does not guarantee success. The history of prosthetic development has been dominated by a “technological-push” model, often neglecting the biological reality of the user. True clinical translation requires a transition toward a patient-centric approach that prioritises residuum health, embodiment, and long-term viability (Figure 1). This literature review examines the intersection of three fundamental domains: neural interfaces, which bridge the gap between brain and machine; osseointegration, which ensures skeletal and functional stability; and patient-centric design, which integrates digital monitoring and personalised rehabilitation (Figure 1). In the following sections, I will synthesise these advancements, starting with the technical evolution of bidirectional neural control, moving into the essential role of skeletal integration and residuum health, and concluding with a framework for how researchers may overcome current clinical and organisational barriers to make bionic limbs a sustainable, equitable standard of care. 

2. Neural Interfaces and Bidirectional Control

Establishing a reliable, bidirectional link with the peripheral nervous system serves as the foundational requirement for any functional bionic limb. Recent surgical breakthroughs seek to maximise the “information throughput” of this interface, ensuring that the human-machine interaction is not limited by a lack of viable control signals. 

Amputations affect hundreds of thousands of people each year in the United States and Europe, particularly. Therefore, there has been a growing interest in neuroprosthetics that can restore both movement and sensation. While today’s bionic limbs can perform increasingly precise movements, they still fall relatively short when replicating a natural limb. One of the biggest challenges regarding this is establishing a strong, long-term connection with the peripheral nervous system that can both monitor motor commands and deliver meaningful sensory feedback (Cho et al., 2023). Existing neural interfaces, whether engineered or biological solutions, often struggle with durability, biocompatibility, and limited signal variety. A new hybrid bionic interface has been established to bridge these gaps by combining a regenerative peripheral nerve interface (RPNI) with a traditional nerve interface with a single implant (Cho et al., 2023). The device uses a buckle-shaped design made from a shape memory polymer (SMP), allowing it to be easily implanted onto a severed nerve while also connecting to a muscle graft. Long-term in rabbits showed that the interface remained stable and biocompatible while reliably recording and stimulating neural signals (Cho et al., 2023). Most importantly, it was able to capture distinct motor signals during natural walking and use as a robotic leg. Overall, the hybrid interface offers a more flexible and information-rich way to connect nerves to prosthetics, bringing neuroprosthetic control closer to natural movement and sensation.

2.1 Continuous Neural Control of a Bionic Limb

A 2024 study in Nature Medicine highlights a significant paradigm shift in prosthetic technology by prioritising surgical-neural integration through the Agonist-Antagonist Myoneural Interface (AMI) (Song et al., 2024). Unlike contemporary bionic limbs that rely on intrinsic pre-defined control frameworks to estimate gait phases, the AMI procedure restores a degree of natural proprioception by surgically reconnecting residual muscle pairs. This interface allows the human nervous system to directly and continuously neuromodulate the bionic limb (Figure 2), augmenting residual muscle afferents by 18% if biologically intact values (Song et al., 2024). This restoration of sensory feedback proved sufficient to enable a highly biomimetic gait, with participants achieving a 41% increase in maximum walking speed compared to matched control cohorts (Song et al., 2024). Furthermore, the study demonstrates that this level of afferent augmentation allows for seamless adaptation to complex, real-world environments such as stairs, slopes, and obstructed pathways without the need for robotic decision-making (Figure 2). Ultimately, these results suggest that even partial reinstatement of the biological feedback loop is sufficient for the human nervous system to regain versatile, biomimetic motor control, offering a potent alternative to autonomous robotic systems.

2.2 Improving Bionic Limb Control

Freitag et al. (2026) investigated the use of reinforced learning (RL) to improve the decoding of human motor intent for bionic limb control using electromyographic signals (EMG) (Freitag et al., 2026). Accurate and robust intent decoding remains a major challenge in prosthetics, and most existing approaches rely on supervised learning (SL) trained on static, labeled EMG datasets (Freitag et al., 2026). However, such data fails to reflect natural muscle activity during real-world use, limiting online performance and usability. The researchers propose a novel training framework that combines SL and RL. An initial control policy is first pretrained using supervised learning based on EMG recordings. This policy is fine-tuned using offline reinforcement learning with dynamic EMG data collected while participants interact with a custom-designed, Guitar Hero-inspired game. The game environment enables real-time, human-in-the-loop interaction and provides a structured reward signal based on movement accuracy and timing. The Advantage Weighted Actor Critic (AWAC) algorithm is used to improve the policy while remaining close to previously learned behaviours (Freitag et al., 2026). Experiments were conducted with nine able-bodied participants performing simultaneous finger movements. Results show a threefold increase in normalized cumulative reward and more than a two-fold improvement in decoding accuracy compared to the supervised baseline (Freitag et al, 2026). Improvements generalised to a separate motion test, demonstrating enhanced robustness. The study concluded that reinforcement learning on interactive, usage-based data can bridge the gap between offline training and real-world prosthetic control, supporting more intuitive and reliable bionic limb operation.  

The future of bionic limbs depends on bridging the gap between advanced engineering and the biological reality of the post-amputation physiology of patients (Paslausta et al., 2022). Engineers have developed sophisticated bidirectional systems capable of decoding motor intent and providing sensor feedback using surgical techniques like Targeted Muscle Reinnervation (TMR) and Agonist-Antagonist Myoneural Interface (AMI) (Paslausta et al., 2022) (Figure 3). Methods like TMR and AMI are highlighted for their ability to recreate biological feedback loops, such as proprioception, that the brain expects to receive (Figure 3). Moreover, researchers highlight the need for biomimetic encoding and moving beyond simple electrical pulses to natural sensory algorithms with a deeper focus on motor control theory and understanding how the brain manages postural balance and embodiment (Paslausta et al., 2022).

Restoration of sensorimotor function in upper limb amputees has historically been limited by the lack of reliable control, sensory feedback, and comfortable attachment (Ortiz-Catalan et al., 2023). Traditional socket-based prostheses often cause discomfort and rely on surface electrodes that are prone to signal interference. Ortiz-Catalan et al. detail the clinical implementation of a transradial neuromusculoskeletal prosthesis, which connects a bionic hand directly to the user’s nervous and skeletal systems (Figure 4). In a landmark case study, a patient with a below-elbow amputation received titanium implants in the radius and ulna for osseointegration, providing stable skeletal attachment (Figure 4). Surgically, the interface was enhanced by creating regenerative peripheral nerve interfaces (RPNIs) through the transfer of severed nerves into free muscle grafts (Ortiz-Catalan et al., 2023). These grafts, along with native muscles and the ulnar nerve, were instrumented with implanted electrodes (Figure 4). The resulting system is entirely self-contained, requiring no external batteries or processing units for daily use. 

Long-term results over three years demonstrated significant improvements:

1. Enhanced Function: Improved scores in the Southampton Hand Assessment Procedure (SHAP) and Assessment of Capacity for Myoelectric Control (ACMC).
2. Sensory Feedback: Consistent tactile sensations elicited via direct neural stimulation of the ulnar nerve.
3. Quality of Life: A marked reduction in phantom limb pain and a substantial increase in overall well-being. 

This integrated approach overcomes the “HMI paradox” by providing a high-bandwidth, stable, and bidirectional communication channel between the patient and the bionic limb (Ortiz-Catalan et al., 2023).

3. Neuroplasticity and User Adaptation

Once a physical neural connection is achieved, the focus must shift to the central nervous”s systems” innate ability to adapt to artificial input. Understanding the brain’s capacity for cortical reorganisation is essential, as the user must essentially re-learn how to control a limb that no longer communicates through the traditional biological pathways. 

3.1 Bidirectional Bionic Limbs

Although engineers have developed sophisticated bidirectional systems capable of decoding motor intent and providing sensory feedback, these technologies often operate in a vacuum, failing to account for how nervous systems reshape after losing a limb (Paslausta et al., 2022). Amputation triggers significant cortical reorganisation, where the brain’s sensory and motor maps may shrink or shift over time (Paslausta et al., 2022). To address this, a transdisciplinary approach is required to manage neuroplasticity. Thus, a solution that combines high-tech hardware with innovative surgical techniques must be implemented. Ultimately, restoring the true function of a missing limb requires treating the prosthesis and the patient’s altered physiology as a single, integrated system rather than separate components (Paslausta et al., 2022).  

The concurrent TMR, targeted sensory reinnervation (TSR) for touch, and vibration-induced kinesthesia significantly advance bionic limb functionality toward able-bodied norms (Marasco et al., 2021) (Figure 5). By establishing a bidirectional neural-machine interface in participants with proximal neural-limb amputations, this approach moves beyond traditional myoelectric control to restore complex sensory-motor loops. The simultaneous delivery of tactile and kinesthetic feedback allows users to transition from speed-driven, compensatory behaviours to accuracy-maximising strategies, characterised by a marked reduction in visual dependency (Marasco et al., 2021). This restoration of feedback channels promotes a measurable shift in visuomotor behaviour whereby users redirect their gaze from the prosthetic hand toward the intended target while also enhancing limb ownership by aligning the device’s performance with the brain’s internal model (Marasco et al., 2021) (Figure 5). Ultimately, providing a multifaceted sensory experience is critical for reducing cognitive load and achieving “human-like” integration in prosthetic systems, effectively stratifying bionic performance away from conventional prosthetics and toward natural physiological function. 

3.2 Biometric Versus Arbitrary Motor Control

Contrary to the long-standing “biomimetic assumption” in neuroprosthetics, recent evidence from Nature Human Behaviour (2024) suggests that anthropomorphic control strategies, those that mimic biological movements, do not inherently provide superior long-term benefit for device learning or embodiment (Schone et al., 2024). By evaluating participants using a myoelectric bionic hand, researchers compared a biomimetic mapping against an arbitrary, non-biomimetic strategy to determine if recruiting pre-existing neural resources actually enhances performance. The findings revealed that while biomimetic control offered an initial “intuitive” advantage in speed and automaticity, these differences vanished as training progressed, with arbitrary users eventually matching their counterparts in dexterity and gesture switching (Marasco et al., 2021). The study further demonstrated that the arbitrary control group exhibited significantly higher levels of generalisation when they were tasked with a novel control mapping; arbitrary users maintained their proficiency, whereas biomimetic users experienced a sharp decline in performance (Marasco et al., 2021). Interestingly, both groups reported significant and comparable increases in a sense of embodiment, specifically regarding agency and body ownership, thus indicating that the bian’s integration of the tool depends more on the reliability of the human-machine interface than on anatomical mimicry. These results suggest that by moving away from strict biomimicry, designers can leverage the nervous system’s capacity for reinforcement learning to create more flexible, functional, and adaptable prosthetic solutions. 

4. Osseointegration and Skeletal Integration

While neural signals provide the intent, the physical stability of the limb is what allows that intent to be translated into meaningful action. Osseointegration represents a landmark advancement in this regard, moving away from adverse effects and issues of traditional sockets toward a permanent, bone-anchored skeletal attachment.

Traditional socket-based prostheses frequently cause discomfort, skin damage, and limited mobility, often resulting in high rates of device abandonment (Frossard and Lloyd, 2021). In contrast, osseointegrated bionic limbs are directly anchored to the bone, offering significantly improved stability and mobility (Frossard and Lloyd, 2021). This direct connection facilitates “osseoperception”, a form of sensory feedback that allows users to walk more naturally and experience an enhanced sense of embodiment (Frossard and Lloyd, 2021). By providing a stable mechanical foundation, osseointegration overcomes the functional limitations of the soft-tissue interface.

Azocar et al. researched the design, implementation, and clinical testing of the Open Source Leg (OSL), an integrated robotic knee-ankle prosthesis developed to advance research and clinical evaluation of powered lower limb prostheses in real-world environments (Figure 6). While powered prostheses can improve walking speed, stability, and energy efficiency for individuals, progress has been limited by high costs, proprietary designs, and the lack of standardized hardware for testing control strategies. The OSL addresses these challenges by providing a low-cost, portable, customisable, and fully open-source platform (Azocar et al., 2020). The prosthesis integrates high-torque electric motors, low-ratio belt transmissions, embedded sensing, and low-level control software, thus enabling independent operation of the knee and ankle joints (Azocar et al., 2020). A configurable series elastic actuator allows researchers to adjust joint stiffness and study different control options. Extensive benchtop testing demonstrated high bandwidth, accurate position and current control, reliable torque output, and safe thermal performance (Azocar et al., 2020). Clinical testing with 3 individuals with lower limb amputations showed that OSL supports stable ambulation across level ground, ramps, and stairs, using impedance-based control whereby participants achieved kinematics and kinetics comparable to able-bodied walking (Azocar et al., 2020) (Figure 6). By releasing hardware designs, software, and benchmark datasets, the OSL lowers barriers to prosthetic research and enables fair comparison of control strategies, supporting future innovation in bionic limb technology. 

4.1 Bionic Limb Replacement 

Amin (2022) examined the evolving role of bionic limb replacement in the context of lower extremity reconstruction. Advances in lower extremity reconstruction, including microvascular techniques, nerve and tendon transfers, and complex bone reconstruction, have expanded limb salvage options, but outcomes are still often limited by infection, unstable soft tissues, prolonged rehabilitation, chronic pain, and donor site morbidity. When salvage is unsuccessful, amputation with prosthetic fitting remains a common solution; however, conventional prosthetic fitting frequently fails to provide comfortable, efficient, and intuitive function, particularly due to issues with socket fit, increased energy expenditure, and lack of sensory feedback. Emerging bionic limb technologies offer a potential alternative by aiming to restore bidirectional communication between the nervous system and prosthetic devices (Amin, 2022). Approaches such as myoelectric control, targeted muscle reinnervation, and direct neural interfacing through extraneural, intraneural, and regenerative electrodes have demonstrated promise in improving motor control and sensory perception (Amin, 2020). Nevertheless, significant challenges remain, including signal instability, biological compatibility, invasiveness, and long-term reliability (Amin, 2020). Collectively, this body of work suggests that future progress in lower limb reconstruction will increasingly rely on interdisciplinary advances in neural interfaces, robotics, and tissue engineering to develop more functional and intuitive bionic limb replacements. 

4.2 Self-Contained Bidirectional Bionic Limbs

Surgical neural engineering and human-machine interfacing (HMI) have reached a milestone with the development of fully self-contained, bidirectional bionic limbs. A primary challenge in prosthetics is the “HMI paradox” whereby, as amputation levels rise, the complexity of the required prosthesis increases while the number of available biological control signals decreases (Dosen, 2023). To overcome this, a comprehensive HMI pipeline integrates advanced surgical techniques, such as muscle grafts and targeted muscle reinnervation, to create additional signal sources (Ortiz-Catalan et al., 2023). The system implemented by Ortiz – Catalan et al. utilises osseointegration, which is the permanent attachment of the prosthesis to the skeleton via titanium implants. This provides a stable gateway for bidirectional communication. Motor control is achieved through intramuscular and epimysial electrodes that record from native muscles and grafts, while sensory feedback is restored by delivering electrical stimulation to the ulnar nerves via extraneural cuff electrodes (Ortiz-Catalan et al., 2023). Long-term clinical results over three years demonstrate that this approach enables stable, dexterous control of individual digits and provides intuitive tactile sensations (Ortiz-Catalan et al., 2023). By combining skeletal attachment with implanted neural interfaces (Figure 7), this research moves closer to the ideal reality of bionic replacement: a limb that offers effortless, simultaneous control and natural somatosensory feedback, significantly enhancing the user’s daily quality of life.

5. Sensory Feedback and Embodiment

The ultimate success of a bionic limb is often defined by the user’s sense of ownership over the device, referred to as a psychological state known as embodiment. This state is achieved only when the brain receives consistent, multi-modal sensory feedback, such as heat, pressure, and kinesthesia, that aligns with its internal motor expectations. 

5.1 Thermally Sentient Bionic Limbs

Ortiz-Catalan argued for exploring thermal sensation as an added sensory modality in bionic limbs through sensory reinnervation. When nerves from an amputated limb naturally or surgically reinnervate the skin of the residual limb, they create “phantom maps”. By stimulating these specific areas with compact thermoelectric devices, researchers successfully triggered sensations of heat and cold, localised by the brain to the missing upper limb (Ortiz-Catalan, 2024). Moreover, in clinical trials, participants were able to distinguish between different materials, such as copper or glass, and accurately identify the temperature of objects they made contact with while wearing the bionic limb (Ortiz-Catalan, 2024). Unlike electrical nerve stimulation, which often may feel artificial, thermal stimulation of the phantom maps feels natural because it activates biological sensors as intended (Ortiz-Catalan, 2024). However, these maps are often somatopically disorganized or incomplete, though remaining stable for 48 weeks (Ortiz-Catalan, 2024). Therefore, it does still offer a promising avenue for long-term research and daily use. Ultimately, while thermal sensing may enhance the bionic limb user’s sense of “embodiment”, its primary value lies in improving the functional and social capabilities of artificial limbs.

5.2 Bionic E-Skin

Xu et al. (2024)  introduced a self-powered bionic droplet electronic skin (DES), designed to help bionic limbs establish a sense of touch to liquids (Figure 8). Generally, e-skins focus on solid pressure or temperatures, but most fail to perceive the movement of liquids. The proposed e-skin uses the triboelectric effect, meaning it generates its own electricity from the friction created when a water droplet slides across the surface, requiring no external power (Xu et al., 2024). This technological breakthrough is an interlaced electrode network and “overpass” connection design (Xu et al., 2024). This allows the skin to track the precise 2D trajectory, velocity, and acceleration of a droplet without the signal getting “crossed” or blurry. It’s so sensitive that it can even distinguish between different liquids such as tap water, rainwater, and seawater, based on their specific electrical signatures (Xu et al., 2024). Beyond just sensing, researchers demonstrated autonomous regulation similar to human neuromodulation (Xu et al., 2024). For example, when the skin detects a liquid leak, it can identify the direction of the flow and trigger an intelligent closed-loop system to shut a valve and stop the leak (Xu et al., 2024). Moreover, the e-skin is made of flexible, waterproof materials, and the AI allows for navigation and reaction to wet, unpredictable environments like rain or industrial spills as intuitively as a human would (Xu et al., 2024).

6. Patient-Centric Design and Residuum Health 

A sustainable bionic solution must prioritize the long-term health of the residual limb, or residuum, above mere mechanical performance. By utilising predictive tools such as digital twins, clinicians can now proactively manage the health of the patient’s tissue and bone, preventing the complications that historically led to prosthetic abandonment. 

6.1 Advances in Clinical and Prosthetic Care

Frossard et al. (2022) highlighted the necessity of a critical shift in this field of medicine, moving beyond just building better AI to focus on the health of the residuum. Generally, prosthetics fail because of the adverse effects, such as skin issues, pain, and bone loss, caused by the interface between the body and the device. This leads to an increase in limb abandonment. To fix this, researchers are pushing “Bionic 4.0 solutions”: direct skeletal attachment, osseointegration, and advanced neural interfaces such as TMR to get rid of pain caused by sockets and to improve control while reducing phantom pain (Frossard et al., 2022). After surgery, rehab blueprints should be established with examples such as botulinum toxin to stop skin movement around implants and haptic sleeves that give users a sense of touch (Frossard et al., 2022). Furthermore, a healthy residuum is a multifaceted goal whereby the patient’s age, weight, and specific alignment of the prosthetic joint are all key factors, not just the surgery. Consequently, new technology such as the Computer Assisted Limb Assessment (CALA) allows clinicians to objectively map out patients’ phantom pain, thus making it easier to treat (Frossard et al., 2022). Overall, the goal should be to stop oscillation of patients between satisfactory mobility and bedridden pain by threatening the prosthesis and the patient’s biology as a single, connected system.

To address the risks associated with bone-anchored systems, such as infection, implant failure, and fractures, a novel and non-invasive diagnostic approach using a “digital twin” of the residuum was proposed by Frossard and Lloyd (2021). This high-fidelity, physics-based virtual model integrates real-time data from wearable sensors to monitor internal tissue response during prosthetic use (Frossard and Lloyd, 2021). By visualising stresses and movements within the limb, clinicians and patients can better manage loading patterns and reduce injury risk (Figure 8). This transformative step toward intelligent bionic limbs supports personalized rehabilitation and improves long-term patient safety. 

7. Clinical Translation Challenges and Barriers

While laboratory milestones of the past decade are impressive, the transition from an experimental prototype to a standard-of-care medical device remains the most significant hurdle in prosthetic medicine. Evaluating bionic systems through a lens of translation-readiness reveals that high-performance metrics in a controlled setting do not always correlate with daily clinical utility. It is important to recognise that an ideal device in a lab may still fail in the real world if the surrounding infrastructure is not ready. 

7.1 Technical Barriers: Reliability and Biotic-Abiotic Integration

The first layer of obstruction involves the physical and electrical longevity of the system. For a bionic limb to be truly translation-ready, it must move beyond “benchtop” success and demonstrate resilience against the unpredictability of human life. Biocompatibility remains a major concern; even the most advanced electrodes face the risk of signal instability and decay over time as the body’s foreign-body response encapsulates sensors in fibrous tissue (Amin, 2022). Furthermore, achieving a truly permanent solution requires overcoming the risks of chronic infection at the percutaneous interface, which is a significant hurdle for the long-term reliability of fully implantable systems (Bumbaširević, 2020). Additionally, maintaining stable closed-loop control is technically taxing outside of controlled laboratory environments, where external interference and extraneous variables may disrupt the delicate neural signals required for intuitive motor execution. 

7.2 Clinical Organisation Barriers: The Infrastructure of Care

Advanced surgical interventions such as TMR or AMI require interdisciplinary teams that many regional clinics cannot support, leading to a disconnect between technological potential and actual clinical integration (Frossard et al., 2022). This disconnect is exacerbated by a reimbursement paradox: national health services and insurance providers are frequently hesitant to cover the high upfront costs of bionic limbs without longitudinal data proving they significantly reduce long-term secondary healthcare expenditures, such as caregiver reliance or mental health intervention. Without standardised clinical training and clear financial pathways, these innovations risk remaining research papers rather than becoming accessible medical standards. 

7.3 Ethical and Equity Considerations: Democratising Innovation  

Many current innovations are hindered by proprietary designs and “closed” software ecosystems that prevent interoperability between different manufacturers. This underscores a desperate need for standardised platforms that could lower production costs and facilitate broader distribution (Azocar et al., 2020).It also raises a critical question of equity, whereby if bionic limbs are only accessible to a small cohort of patients with premium insurance or specific military status, the field may inadvertently widen existing health disparities. An ethical transition toward “translation-readiness” must involve a shift from high-cost, exclusive prototypes toward inclusive, robust, and globally accessible bionic solutions.

8. Future Directions

While the preceding sections have outlined the state of the art and the barriers to implementation, the path forward requires a transition from demonstrating feasibility to ensuring longitudinal reliability. The next generation of research must prioritise the convergence of artificial intelligence, materials science, and standardised clinical protocols to transform bionic limbs from laboratory prototypes into lifelong biological extensions. 

8.1 Technical Future: Intelligence and Sensation:

The technical evolution of bionics will likely focus on the development of more robust, long-term neural interfaces. Current evidence suggests a critical need for long-term human data to validate the stability of bidirectional communication over decades (Cho et al., 2023). Furthermore, the integration of ‘Reinforcement Learning’ (RL) must move beyond virtual simulations into real world settings, allowing devices to adapt dynamically to a user’s unique environment (Freitag et. al, 2026)Beyond motor control, the future lies in multi-modal feedback, incorporating thermally sentient capabilities and bionic e-skins to provide a nuanced sense of touch, temperature, and pressure (Ortiz-Catalan, 2024).

8.2 Clinical Future: Trials and Long-Term Outcomes

The clinical trajectory must shift toward larger trials and standardised long-term outcome measures. To ensure patient safety, future research should integrate residuum-centered protocols that monitor the health of the host tissue alongside device performance (Amin, 2022).This involves moving toward fully implantable systems that minimise the risk of infection while maximising signal fidelity.

8.3 Design and Policy Future: Equity and Standardisation 

From a policy perspective, the field must address the “siloing” of technology. Moving away from proprietary designs toward standardised, adaptable platforms is essential for lowering costs and ensuring equitable access (Azocar et al., 2020). Future regulatory pathways must be streamlined to accelerate the transition from the “bench to the bedside”, ensuring that breakthroughs in the lab actually reach the diverse global population of limb loss patients.

8.4 Core Strategic Objectives:

• Small Learning Curves:

Future prosthetic design must prioritise intuitive control to minimise the cognitive burden on the patient. By aligning the device’s behaviour with the brain’s existing internal motor models, researchers can ensure that users do not require months of intensive training, making the technology accessible to a wider demographic regardless of technical proficiency.

• Simple Procedures for Insurance Coverage:

Clinical translation depends on moving toward surgical techniques that are standardised enough for general hospitals to perform. By simplifying the implementation of interfaces like TMR or AMI, the procedure becomes more “reimbursable” by insurance, shifting advanced bionics from an experimental luxury to a standard, covered medical necessity for all patients.

• Clinical Translation Focus:

The field must move away from “technological push” models toward a “clinical pull” strategy. This means prioritising the practical needs of the patient, such as the device weight, battery life, and skin comfort, over adding high-tech features that have little impact on daily quality of life or long-term functional independence in home environments. 

• Integration of AI (System Thinking):

Rather than using AI for isolated tasks, future systems must adopt “system thinking” AI. This allows the limb to simultaneously manage motor intent, sensory feedback, and environmental adaptation. Instead of a one-size-fits-all functional design, AI will personalise the device’s response in real time, matching the specific physiological signatures of each individual user.

• Approval and Acceleration of Clinical Trials:

The primary bottleneck is no longer the technology itself, but the speed of regulatory approval. Accelerating the transition to large-scale clinical trials is the key to proving long-term safety and efficacy. Without these trials, even the most revolutionary designs will remain stuck in a “proof of concept” phase without reaching the public.

• Integration of Digital Twins:

 Digital twins allow researchers to design and test prosthetics in a high-fidelity virtual environment before any surgery occurs. By simulating the interaction between the device and the patient’s unique bone and tissue structure, clinicians can perfect the design, predict potential failures, and minimise the risks of post-operative complications or revisions.

9. Conclusion

The evolution of bionic limb technology represents one of the most ambitious frontiers in modern medical engineering. As this review has demonstrated, the field has successfully moved beyond simple mechanical substitution toward a sophisticated model of neural and skeletal integration. However, the true measure of success for these innovations is not found in laboratory benchmarks or peak performance metrics, but in their capacity for meaningful clinical translation. For a bionic system to be effective, its design must be clinically driven, thus originating from the actual physiological and psychological needs of the patient rather than being a product of technological push, where features are added simply because they are technically possible.

The trajectory of a successful bionic innovation must follow a clear path: from the research bench, where fundamental science is born, to the clinical bedside, where the technology is safely and intuitively integrated into a patient’s life; and finally to the boardroom, where standardised manufacturing and insurance reimbursement models ensure the device is economically viable and globally accessible. By prioritising “system thinking” through AI and digital twins, and by lowering the cognitive and financial barriers to entry, the field can ensure that bionic restoration is no longer an experimental luxury/ Ultimately, the goal is to transform these devices into seamless biological extensions, restoring not just function, but a genuine sense of embodiment and independence to those living with limb loss. 

Bibliography

Amin, K. R. (2022). Bionic limb replacement: an evolving concept in lower extremity reconstruction. Plastic and Aesthetic Research, 9(3), 24. https://doi.org/10.20517/2347-9264.2021.119

Azocar, A. F., Mooney, L. M., Duval, J.-F., Simon, A. M., Hargrove, L. J., & Rouse, E. J. (2020). Design and clinical implementation of an open-source bionic leg. Nature Biomedical Engineering, 4(10), 941–953. https://doi.org/10.1038/s41551-020-00619-3

Bumbaširević, M., Lesic, A., Palibrk, T., Milovanovic, D., Zoka, M., Kravić-Stevović, T., & Raspopovic, S. (2020). The current state of bionic limbs from the surgeon’s viewpoint. EFORT Open Reviews, 5(2), 65–72. https://doi.org/10.1302/2058-5241.5.180038

Cho, Y., Jeong, H. H., Shin, H., Pak, C. J., Cho, J., Kim, Y., Kim, D., Kim, T., Kim, H., Kim, S., Kwon, S., Hong, J. P., Suh, H. P., & Lee, S. (2023). Hybrid Bionic Nerve Interface for Application in Bionic Limbs. Advanced Science, 10(35). https://doi.org/10.1002/advs.202303728

Dosen, S. (2023). Toward self-contained bidirectional bionic limbs with high information throughput. Science Robotics, 8(83). https://doi.org/10.1126/scirobotics.adk6086

Freitag, K., Karayiannidis, Y., Zbinden, J., & Laezza, R. (2026). Fine-Tuning Myoelectric Control Through Reinforcement Learning in a Game Environment. IEEE Transactions on Biomedical Engineering, 73(1), 168–179. https://doi.org/10.1109/tbme.2025.3578855

Frossard, L., Conforto, S., & Aszmann, O. C. (2022). Editorial: Bionics limb prostheses: Advances in clinical and prosthetic care. Frontiers in Rehabilitation Sciences, 3. https://doi.org/10.3389/fresc.2022.950481

Frossard, L., & Lloyd, D. (2021). The future of bionic limbs. Research Features, 134. https://doi.org/10.26904/rf-134-7477

Guo, K., Lu, J., Wu, Y., Hu, X., & Yang, H. (2024). The Latest Research Progress on Bionic Artificial Hands: A Systematic Review. Micromachines, 15(7), 891. https://doi.org/10.3390/mi15070891

Long, Z., Qiu, X., Chan, C. L. J., Sun, Z., Yuan, Z., Poddar, S., Zhang, Y., Ding, Y., Gu, L., Zhou, Y., Tang, W., Srivastava, A. K., Yu, C., Zou, X., Shen, G., & Fan, Z. (2023). A neuromorphic bionic eye with filter-free color vision using hemispherical perovskite nanowire array retina. Nature Communications, 14(1). https://doi.org/10.1038/s41467-023-37581-y

Marasco, P. D., Hebert, J. S., Sensinger, J. W., Beckler, D. T., Thumser, Z. C., Shehata, A. W., Williams, H. E., & Wilson, K. R. (2021). Neurorobotic fusion of prosthetic touch, kinesthesia, and movement in bionic upper limbs promotes intrinsic brain behaviors. Science Robotics, 6(58). https://doi.org/10.1126/scirobotics.abf3368

Ortiz-Catalan, M. (2024). Thermally sentient bionic limbs. Nature Biomedical Engineering, 8(8), 938–940. https://doi.org/10.1038/s41551-023-01174-3

Ortiz-Catalan, M., Zbinden, J., Millenaar, J., D’Accolti, D., Controzzi, M., Clemente, F., Cappello, L., Earley, E. J., Mastinu, E., Kolankowska, J., Munoz-Novoa, M., Jönsson, S., Cipriani, C., Sassu, P., & Brånemark, R. (2023). A highly integrated bionic hand with neural control and feedback for use in daily life. Science Robotics, 8(83). https://doi.org/10.1126/scirobotics.adf7360

Pasluosta, C., Kiele, P., Čvančara, P., Micera, S., Aszmann, O. C., & Stieglitz, T. (2022). Bidirectional bionic limbs: a perspective bridging technology and physiology. Journal of Neural Engineering, 19(1), 013001. https://doi.org/10.1088/1741-2552/ac4bff

Schone, H. R., Udeozor, M., Moninghoff, M., Rispoli, B., Vandersea, J., Lock, B., Hargrove, L., Makin, T. R., & Baker, C. I. (2023). Should bionic limb control mimic the human body? Impact of control strategy on bionic hand skill learning. https://doi.org/10.1101/2023.02.07.525548

Schone, H. R., Udeozor, M., Moninghoff, M., Rispoli, B., Vandersea, J., Lock, B., Hargrove, L., Makin, T. R., & Baker, C. I. (2024). Biomimetic versus arbitrary motor control strategies for bionic hand skill learning. Nature Human Behaviour, 8(6), 1108–1123. https://doi.org/10.1038/s41562-023-01811-6

Song, H., Hsieh, T.-H., Yeon, S. H., Shu, T., Nawrot, M., Landis, C. F., Friedman, G. N., Israel, E. A., Gutierrez-Arango, S., Carty, M. J., Freed, L. E., & Herr, H. M. (2024). Continuous neural control of a bionic limb restores biomimetic gait after amputation. Nature Medicine, 1–10. https://doi.org/10.1038/s41591-024-02994-9

Xu, Y., Sun, Z., Bai, Z., Shen, H., Wen, R., Wang, F., Xu, G., & Lee, C. (2024). Bionic e-skin with precise multi-directional droplet sliding sensing for enhanced robotic perception. Nature Communications, 15(1). https://doi.org/10.1038/s41467-024-50270-8

Zhang, H., & Lee, S. (2022). Robot Bionic Vision Technologies: A Review. Applied Sciences, 12(16), 7970. https://doi.org/10.3390/app12167970

About the author

Sharanya Seth

Sharanya Seth is a Grade 11 student at United World College South East Asia in Singapore with a strong interest in medicine, particularly in surgical fields such as Obstetrics and Gynaecology and Plastic Surgery. She has gained early clinical exposure through internships in both Singapore and India, where she observed procedures including hysterectomies and fertility treatments, and assisted with patient interactions in a general practice setting. These experiences provided her with insight into clinical environments, patient care, and the doctor-patient relationship.

Sharanya is actively engaged in scientific research, having submitted a CREST Award project investigating the inhibitory effects of natural disinfectants such as turmeric and garlic on E. coli growth. She is currently conducting an Extended Essay exploring glucose diffusion and its relevance to diabetes, further developing her ability to apply scientific principles to real-world medical challenges.

In addition to her academic pursuits, she leads a service initiative supporting individuals with intellectual disabilities, where she organises cognitively stimulating activities to promote engagement and social interaction, as well as fosters an environment of respect and inclusivity. She also volunteers regularly at the National Kidney Foundation in Singapore, where she helps in the Dialysis Centre and Enrichment sector with patients. She has been recognised on the High Honour Roll award for three consecutive years and has achieved distinction in piano examinations, along with athletic awards.

The post Clinical Translation of Bionic Limbs: Neural Interfaces, Osseointegration, and Patient‑Centric Design appeared first on Exploratio Journal.

Abstract

This paper explores the complex relationship between tariffs on Gross Domestic Product (GDP) and the U.S. trade balances with its major trading partners. It investigates if imports and greater trade balances changed between the U.S and its top trading partners after tariffs were placed. The conclusion is no significant change in trade balances since the implementation of the Trump administration’s tariffs.

The evidence shows that in the months of April to July, the tariffs have not significantly changed U.S. net trade. The effects studied in this paper are a result of new trade policies by the Trump Administration which put retaliatory tariffs on most of the world. As a result, many firms and businesses frontloaded the tariffs which caused a 40% increase in imports in Q1 2025. Also in Q1, real GDP decreased by 0.5% (U.S. Bureau of Economic Analysis, 2025) according to the most recent estimate. However, imports do not reduce GDP and are only included in the calculation to support accounting principles. As a result of this misconception, many news articles written by journalists who are not economists have had misleading claims with regards to the GDP decrease. The current results of the findings could potentially be attributed to the uncertainty in the administration’s tariff policy or simply that not enough time has passed for significant changes to be observable in the data.

Introduction & Literature Review

The role of imports in shaping a nation’s economy has become increasingly significant following President Trump’s trade wars and tariffs on countries across the world. Many of these tariffs were put during the first quarter of 2025 while the others were placed on April 2, 2025, also known as Liberation Day. However, news of President Trump’s intention of using tariffs has been clear before his Inauguration and use of tariffs on foreign countries was common in his first term as well. Since his election, many businesses and firms have increased inventories and the amount of imported goods in anticipation of high tariff rates to go into effect soon.

As noted above, the heart of GDP measurement is the widely cited expenditure formula: GDP = C + I + G + (X-M) where C denotes consumption, I investment, G government expenditures, X exports, and M imports. The superficial glance at this equation shows imports as a direct drag on GDP. However, economists consistently clarify that this superficial glance is quite misleading as the negative sign simply represents an accounting principle to prevent double counting.

Bill Conerly (2025), a writer at Forbes, clarifies that “U.S. imports are neither added nor subtracted conceptually” (para. 3) for GDP. He explains that with perfect data available to statisticians, imports wouldn’t be included in a GDP calculation (Conerly, 2025).

Looking at the subtraction, Greg Mankiw notes, “this subtraction is made because imports of goods and services are included in other components of GDP,” (Mankiw, 2001, p. 499) Mankiw also notes how a purchase of an imported good raises consumption, investment or government expenditures.

The St. Louis Fed adds that “imports (foreign production) should have no impact on GDP,”(Wolla, 2018, para. 9). They explain the variable M as an accounting variable rather than an expenditure variable. It is also important to note that the imported goods will have an effect on the GDP of the country that produces them. Since it isn’t the United States, they don’t affect U.S. GDP. However, it can take into account if the goods are intermediate or partially produced in the U.S. Since the expenditure variables of C, I, and G only take final goods into account, GDP will be affected based on the amount of the goods that was domestically produced.

Keshav Srikant, a writer with Econofact, supports the net-zero effect on imports on GDP. However, he also notes how imports can potentially indirectly reduce GDP if they replace domestic consumption or if domestic government expenditures are reduced as a result of higher purchases of foreign goods (Srikant 2025). Further study of macroeconomic trends are required to make an argument for this situation as these latent variables could drive import growth and GDP declines when those two variables are not correlated.

Ultimately, imports do not directly reduce GDP and their inclusion in the components of GDP is a measure to prevent double counting.

There are many researchers who have explored the growth of imports and its, relationship with the overall economy. In fact, many specific case studies have found that an increase in imports often leads to an increase in real GDP .

A study by Peter Saunders, focused on a time series analysis of the role of imports in the economic rise of India from 1970 to 2005, analyzes the long term relationship between imports and India’s real GDP. Saunders establishes that both variables, imports and real GDP, are cointegrated using Johansen’s test of cointegration (Saunders 2010). This test proves if two variables have a long term equilibrium relationship, meaning that despite short term deviations or outliers, the variables have a long term observed relationship. A Vector Error Correction Model (VECM) examines the relationship between cointegrated variables. In the VECM used by Saunders, the results indicated that imports have positively impacted India’s economic growth in the short-term. Saunders highlights how this result defies traditional expectations that imports could be a drag on the economy (Saunders 2010).

In another study by M.Y Khan et al, about the relationship between imports and economic growth in Pakistan, a similar conclusion was reached. This study used data from 1975 to 2014 with the methodology of a Granger Causality Test. This test focuses on proving directional relationships between time series variables. The results showed that there was a bi-directional relationship between imports and economic growth in Pakistan, meaning that both time series variables mutually supported one another (Khan et al, 2019).

Research focusing on the relationship Rwandan economic growth with imports and exports showed a positive long run relationship (Al Hemzawi & Umutoni 2021) . The study concluded that a one percent increase in imports led to a 0.32% rise in Rwandan GDP. To get that correlation, the authors used a multivariate Ordinary Least Squares regression which is a way to minimize variance between variables. They also used quarterly time series data in the regression.

Immediately after the Q1 GDP contraction was announced, many news publications released misleading or false articles regarding the cause behind this result. They accredited the cause to be the tariff jumping effect and the dramatic import surge that occurred because firms and businesses rushed to purchase foreign goods before tariff prices were assigned to goods. The underlying demand was quite consistent to previous levels while business investment surged as an offset to the imports. Despite the fact that imports do not directly reduce GDP, news outlets continued to push that narrative.

For example, an AP News article stated “First-quarter growth was weighed down by a surge of imports, ” (Wiseman 2025, para. 2) while The Hill said “GDP shrank in the first quarter mostly because of lower consumer spending and a pull-forward in imports ahead of President Trump’s tariffs, ” (Burns 2025,para. 4). Many other outlets made misleading claims regarding the import surge. Although journalistic misconceptions are not uncommon, even the Federal Open Market Committee has made mistakes with regards to the effect of imports on GDP (Lemieux 2018).

On the other hand, many top economists have had different opinions. Many economists have attributed the contraction to the economic activity as a result of the imports, not by the imports directly. For example, Paul Gruenwald, a global chief economist for S&P Global Ratings, mentioned that Q1 GDP data was “distorted by the front-running of tariffs,” (2025). Gregory Daco, a chief economist at EY , added “the contraction was largely a function of economic activity being pulled forward as importers, business, and consumers rushed to get ahead of tariff implementation,” (2025). Economist Preston Caldwell ofMorningstar added that imported goods could be stored in inventories but “it just didn’t show up in the data because of measurement error,” (2025).

Some top economists also challenged the fear that this GDP result was the first domino in a potential recession. Caldwell added that this result “doesn’t mark the beginning of a recession,” (2025). Others mentioned potential for economic uncertainty further down the line as more policy was unveiled. “Demand in the first quarter looks to be driven by businesses battening down the hatches before the storm,” Chief economist Luke Tiley of the Wilmington Trust said (2025).

One potential explanation for the GDP decrease is a phenomenon called the substitution effect, a phenomenon that suggests that the tariff induced frontloading substituted for domestic purchases. If this is the case, GDP would decrease since less money would be spent toward domestic production. This has been prevalent in the past as well.

In the 1990s, the Northern American Free Trade Agreement (NAFTA) contemplated potential tariff reductions. 96% such reductions were announced far in advance, giving consumers and firms the chance to act on this information ( Khan & Khederlarian 2021). A study found that in anticipation of an upcoming tariff reduction of 1%, imports dropped by a sizable 6% in the months before the tariff implementation when compared to regular months. The study used an Herfindahl-Hirschman Index, a method to measure market concentration, and applied it to the spread of imports. Their final result articulated that firms shift their purchases to periods when lower costs can be attainable and that these anticipatory dynamics are true (Khan & Khederlarian 2021).

A potential alternate explanation is that the small decrease in government expenditures was the key factor in the GDP decrease.

There are some potential gaps in data which limit the study of GDP accounting. For example, these accounting principles say nothing about potential causality with latent variables or economic impacts. There is also difficulty in GDP data collections since it can be difficult to only count final goods. Finally, GDP data could be fixed-weighted calculations that can add error as the economy changes and price structures evolve. However, when calculated in a chain-weighted approach to account for economic evolution, there are still struggles with new goods being added.

Methodology

This analysis uses monthly trade data and monthly effective tariff rates for the United States with its largest trading partners. It also uses the same data for the European Union to use as a control. The source for monthly trade data values were the U.S. Census Bureau and Eurostat. The effective tariff rate values were gathered from trusted sources and reflect prior US tariffs and changes as newer tariffs went into effect. This analysis employs a linear regression test with net trade balances and effective tariff rates to analyze the potential correlation between the two.

Results

The data shows a minimal negative relationship between tariff rate and change in trade balances. This means that since the tariffs went into effect, there hasn’t been a significant increase or decrease in U.S. trade balances with main trading partners. The correlation coefficient was 0.0806 which confirms that in the three months since the tariffs went into effect, there weren’t any significant changes in trade balances that were caused by the changes in effective tariff rates. The coefficient of determination is 0.0065, or approximately 0, which meant that any changes that did occur in trade balances were not from the changes in effective tariff rates. Finally, the t-score value equals 0.0977 and indicates that the observed result aligns with the null hypothesis and the difference between the sample data and the population data is not statistically significant.

Discussion

Ultimately, the analysis proves that there is no correlation between the vast increases in effective tariff rates and changes in net trade balances. By contrast, as shown in Table 2, the U.S. trade deficits actually became larger for some countries such as Vietnam or the United Kingdom despite increases in effective tariff rates. Other countries such as China or Italy faced similar decreases in trade deficits despite having large differences in net trade and change in effective tariff rates. Furthermore, some countries were levied with larger tariffs than others, making predicting the change in trade balances harder to anticipate.

A potential explanation for the results of the analysis is the extreme volatility in tariff policy during the study period. Following the implementation of the “Liberation Day” reciprocal tariffs in early April, several countries experienced rapid and significant changes in their tariff rates. For example, China briefly faced tariff levels exceeding 140%, while Brazil was subjected to a 50% tariff following political disputes with the U.S. administration. In addition to these enacted measures, frequent public threats of new tariffs introduced further uncertainty into global trade markets. Simultaneously, reports of partial or full trade agreements with major partners like the EU, China, Japan, and South Korea, led to subsequent reductions in effective tariff rates. This pattern of escalation followed by negotiated de-escalation likely diluted the measurable macroeconomic impact of tariffs, complicating attempts to identify stable relationships between tariff levels and trade or GDP outcomes.

Another potential reason can be shown through the pressures of the markets. Financial Times commentator Robert Armstrong coined the current administration’s trade policies as “TACO Trade”. The acronym refers to some of the administration’s sudden reversals of tariffs. Armstrong coined the term when describing the pattern of placing large tariffs on countries which led to economic panic, shock, and stock market hits. He then explained how later reversals of these tariff policies have led to market comebacks. Additionally, the market uncertainty can be explained as how stocks look like they are trending upward and then stop due to a social media post or claim by the government. It’s possible that many firms and businesses believed that the tariff rate changes wouldn’t be in place long term and thus, no changes were found in the U.S. trade balances.

Implications for Policy and Future Research

Investigating the nuanced economic effects on GDP is key for future policy regarding tariff measures and potential trade deals. As occurred in Q1, there are potential short term distortions in GDP measurement so it’s important to keep these in mind. An area for future research is on the study of tariffs-driven import behavior and with the substitution effect’s prominence in the short and long term. This would provide key insights into how firms react to the government policy and how both parties can better facilitate economic policy.Finally, it’s important to continue to analyze changes in trade balances to see if significant changes will be present with the passing of time and more recent data.

Works Cited

Al Hemzawi, B., & Umutoni, N. (2021). Impact of Exports and Imports on the Economic Growth. MSc. Thesis, Jönköping University. Buckling up for a long ride: chief economists add detail to a downbeat outlook. (2025, May 28). World Economic Forum. https://www.weforum.org/stories/2025/05/wef-chief-economists-uncertainty-global-outlook

Burns, T. (2025, June 26). US economy shrank faster than expected, new data shows. The Hill. https://thehill.com/business/5371005-us-gdp-revised-lower-consumer-spending

Conerly, B. (2025, March 11). Understanding GDP: Why Imports Don’t Actually Reduce Economic Growth. Forbes.https://www.forbes.com/sites/billconerly/2025/03/11/understanding-gdp-why-imports-dont-actually-reduce-economic-growth/

Daco, G. (2025, May). LinkedIn. https://www.linkedin.com/posts/gregorydaco_inflation-fed-fomc-activity-7323335677599793152-c–l/

Freund, C., Pierola, M. D., & Rocha, N. (2021). How Does Trade Respond to Anticipated Tariff Changes? Evidence from NAFTA (Policy Research Working Paper No. 9561). World Bank. Gross Domestic Product, 1st Quarter 2025 (Third Estimate) | U.S. (2025, June 25). Bureau of Economic Analysis. https://www.bea.gov/news/2025/gross-domestic-product-1st-quarter-2025-third-estimate-gdp-industry-and-corporate-profits

Khan, M. Y ., Akhtar, S., & Riaz, S. (2019). Dynamic Relationship Between Imports and Economic Growth in Pakistan. Journal of Economics and Sustainable Development, 10(10), 70–77.

Lemieux, P. (2018, September 6). The St. Louis Fed on Imports and GDP. Econlib. https://www.econlib.org/imports-as-a-drag-on-the-economy/

Mankiw, N. G. (2001). Principles of Economics. Harcourt College Publishers.

Saunders, P.J. (2010). A Time Series Analysis of the Role of Imports in India’s Phenomenal Economic Growth. Indian Journal of Economics and Business, 91, 101-109.

Schonberger, J. (2025, April 30). Shrinking GDP and elevated inflation put Fed in tough spot. Yahoo Finance. https://finance.yahoo.com/news/shrinking-gdp-and-elevated-inflation-put-fed-in-tough-spot-142211609.html

Sekara, D., Dzuibinski, S., & Caldwell, P. (2025, July 16). Morningstar’s Q3 2025 US Market Outlook: Has the Storm Passed, or Are We in the Eye of a Hurricane? Morningstar. https://www.morningstar.com/markets/morningstars-q3-2025-us-market-outlook-has-storm-passed-or-are-we-eye-hurricane

Srikant, K. (2025, May 14). Fact Check: Does an increase in imports directly reduce GDP? Econofact.https://econofact.org/factbrief/fact-check-does-an-increase-in-imports-directly-reduce-gdp

Wiseman, P., & Rugaber, C. (2025, April 29). U.S. economy shrinks 0.3% in first quarter as Trump tradewars disrupt businesses. AP News.https://www.ap.org/news-highlights/spotlights/2025/u-s-economy-shrinks-0-3-in-first-quarter-as-trump-trade-wars-disrupt-businesses/

Wolla, S. A. (2018, September 4). How Do Imports Affect GDP? | St. Louis Fed . Federal Reserve Bank of St. Louis. https://www.stlouisfed.org/publications/page-one-economics/2018/09/04/how-do-imports-affect-gdp

About the author

Ishaan Bafna

Ishaan Bafna is a 12th grade student at Kingswood Oxford School with strong academic and research interests in economics and mathematics. Ishaan actively pursues opportunities that integrates analytical thinking with critical reasoning and problem-solving. Known for his intellectual curiosity and work ethic, Ishaan wishes to pursue a career at the intersection of economics, mathematics and technology.

Outside of the classroom, Ishaan is a leader of his schools Math Team and Mock Trial Team, a lead peer tutor, and a varsity golf athlete. Ishaan has interned with The Hartford Insurance as a Lean Portfolio Management Intern. He is also a National Merit Commended Scholar and a recipient of various awards at his school.

The post The macroeconomic effects of tariffs on GDP and trade balances, through the lens of Q1 2025 GDP change appeared first on Exploratio Journal.

Abstract

This paper aims to address how second chances within duty and redemption tie together in the context of medieval knighthood and honor in the poem Sir Gawain and the Green Knight. The poem Sir Gawain and the Green Knight is a poem about second chances and redemption, telling the moral that while mistakes are inevitable, second chances allow individuals to achieve redemption in their duty. Through critical analysis of Sir Gawain and the Green Knight and the character Gawain the Glorious, Gawain’s character is shown to be one who constantly makes mistakes throughout his journeys. Gawain is offered second chances through the form of Lord Bertelak’s game, where his honesty is tested as a knight. Even when Gawain inevitably fails, he is offered partial redemption in the form of a nick he receives on his neck from the Green Knight. This portrayal is significant of a character seen as a model knight. The message in Sir Gawain and the Green Knight uses a previously glorified Gawain to send the message that, despite the expectation of perfection within duty, continuous redemption and improvement through second chances from past mistakes is honest to one’s duty.

In a profession as prized as medieval knighthood, the concept of life, duty, mistakes, and how they interconnect has been a long-debated concept. The relationship between one’s life and one’s duty has been a long-standing question that has been challenged since the beginning of literature. A significant example of this is the famous poem Sir Gawain and the Green Knight, written during the late 14th century, where the relationship between duty and life is explored through the character Gawain, a knight of King Arthur.

Throughout the entirety of Sir Gawain and the Green Knight, Gawain’s role as a regarded knight is continuously tested throughout his adventures. As a knight of King Arthur, he is prized within Camelot. Further, he is a relative of King Arthur himself and is portrayed as a model knight (Jobe). However, within the poem and Gawain’s journey, his mistakes in his duty are ultimately what lead him to survive and redeem himself to live up to his prized identity. Throughout the poem, multiple factors like Sir Gawain’s identity as a knight, the antagonist Green Knight, and Lord Bertalak’s game rest on the underlying themes of second chances and mistakes. Sir Gawain and the Green Knight is a poem about redemption within duty. While mistakes within duty are inevitably made, second chances still frequently present themselves to give opportunities to redeem oneself in their duty while also holding consideration of their life.

The first instance of a mistake leading to a second chance is in the opening scene in Camelot during the feasts of Yule. When the Green Knight approaches the court with a challenge, not a single knight rises to meet him, despite chivalry and bravery being included in a knight’s honor code. This includes Gawain. It is only when Arthur is forced to arise and almost meets the Green Knight’s challenge that Gawain stands up and takes his challenge:

“Gawain bv Guenevere

Toward the king doth now incline:

‘I beseech, before all here,

That this melee may be mine.”

…

“I am the weakest, well I know, and of wit feeblest;

And the loss of my life would be least of any;

That I have you for uncle is my only praise;

My body, but for your blood, is barren of \mrth;

And for that this folly befits not a king,

And ’tis I that have asked it, it ought to be mine,

And if my claim be not comely let all this court judge,

in sight.” (ll. 338-361, Borroff)

In this scene, Gawain stands up and declares, “I beseech before all here that this melee may be mine…if my claim be not comely let all this court judge in sight.” Not only does Gawain claim responsibility as the player in the Green Knight’s game in front of the court, but he also asks the entire court to hold him responsible for his word, which shows he’s committed to seeing the challenge through. Further, in his words against himself, “I am the weakest…and wit feeblest…the loss of my life would be least of any…” In this, he acknowledges his imperfections as a knight and his willingness to sacrifice himself for the court and King Arthur, something that nobody else had stood up for. Despite Gawain’s delayed acceptance of the Green Knight’s challenge, a lapse in his duty to be brave and chivalrous, he swiftly makes it up by taking up and committing to the responsibility of the Green Knight’s challenge from King Arthur’s hands. This shows redemption in his duty and the rest of the court of being an honorable knight despite his initial mistake because he stood up despite nobody else doing so.

Gawain’s next mistake is shortly after his redemption when he takes the responsibility of the Green Knight’s challenge. In his game with the Green Knight, where they exchange a blow for a blow with the Green Knight’s axe, Gawain deliberately makes his cut a fatal one. He was prompted by King Arthur to be intelligent about his blow, as well as tempted by the Green Knight with the outcome of a fatal blow. The Green Knight says: “and if I spend no speech, you shall speed the better: You can feast with your friends, nor further trace” (ll. 409-410). The Green Knight’s words are deliberately tempting — he brings up Gawain’s friends as well as the possibility of him feasting, if he didn’t have to receive a cut in return. Gawain falls for the bait, and by attempting to make it so the Green Knight would not be able to give him a blow back in return, he does not follow the traits of a medieval knight. It does not display bravery or justice to try to slip out of a game Gawain volunteered for, more especially after his poignant declarations to the entire court of his willingness to lose his life. However, the Green Knight survives, and Gawain is also expected to receive the same blow in return as per the rules of the Green Knight’s game. Thus, despite Gawain’s attempts to go through a loophole in the Green Knight’s game being a mistake, it prompts the rest of the journeys, and, at the time for Gawain, unknown second chances for him to redeem himself as a knight as well as his life. This is also explored in Georges Gusdorf’s “The Game of Chance: Moral Ambiguity in Sir Gawain and the Green Knight.” The loophole reflects a larger ethical ambiguity, as Gawain effectively trades his honor as a knight for a better chance to keep his life. Both preservation of life and duty are important values in Sir Gawain and the Green Knight, and the loophole that Gawain utilizes shows the complexity that accompanies abiding by both duty and life (Gusdorf). The poem later reflects:

Now take care, Sir Gawain,

That your courage wax not cold

When you must turn again

To your enterprise foretold. (ll. 487-490, Borroff)

In this scene, the speaker directly addresses Gawain with a declaration that he needs to be courageous in the future. This reads similar to a warning that Gawain has journeys ahead of him that require his courage as a knight, the very thing the game was testing and relying on. It serves as an acknowledgment that Gawain’s future journey is not so simple, because if the journey was just him receiving the cut, he would not need to ensure that his “courage wax not cold.” Further in the story after the year has passed and Gawain’s expected meeting with the Green Knight approaches, he reflects on his future journey.

“There was much secret sorrow suffered that day

That one so good as Gawain must go in such wise

To bear a bitter blow, and his bright sword

lay by.

He said, “Why should I tarry?”

And smiled with tranquil eye;

“In destinies sad or merry,

True men can but try.” (ll. 558-565, Borroff)

This scene gives the reader some insight into Gawain’s emotions and thoughts regarding his journey and his perceived imminent death. He rhetorically asks himself why he should delay his presumed imminent death, then follows it up by saying “True men can but try” when faced with destiny. While it isn’t clear exactly what Gawain is referring to, based on his future destiny to die, and his pondering over why he should delay the inevitable, it can be assumed Gawain is referring to living past his destiny of death. This shows that despite his acceptance of his imminent death, there is still a part of him that wishes to try and live and redeem himself to be a “true man” who would try and live. This offers the reader some insight on the complexities of Gawain’s current emotions, showing that he feels “tranquil.” Despite his duty as a knight and his expected sacrifice, there is still a part of him that wishes to live and have a second chance at life — something that Gawain says a “true man” would do. This implies that Gawain feels that, to be true to himself, he must also try to live. This displays Gawain’s uncertainty in his future journey despite it being something he is bound by duty to since he took up the Green Knight’s challenge, along with consideration of his own life and his hesitancy about death. However, it also shows a development in Gawain’s attitude toward life and duty, as he also considers the preservation of his life despite an imminent death. This is also explored in Marjorie Nicolson’s “Second Chances and Self-Knowledge in Sir Gawain and the Green Knight.” Gawain’s consideration of his imminent death as a result of a mistake shows a sense of maturity, as he still opts to try as a “true man” would, displaying adherence to staying true to his duty despite his situation. Despite his past mistakes, he resolves to move forward with consideration of his duty (Nicolson). Later, when on his journey, he faces a near-death predicament before his duty is fulfilled. The poem reads:

Thus in peril and pain and predicaments dire

He rides across country till Christmas Eve, our knight.

And at that holy tide

He prays with all his might

That Mary may be his guide

Till a dwelling comes in sight. (ll. 733-739, Borroff)

This scene is another example of a second chance at living appearing for Gawain. After trekking to the point where he was on death’s door, he prayed with vigor for a chance to get guided to his destination. His prayers were answered, and soon after, he discovered Lord Bertilak’s court. It’s important that Gawain was on death’s door and was specifically given a second chance because it tells us that not only does he want to live to fulfill his duty, but he was also offered a second chance to do so through his well-timed discovery of Lord Bertilak’s court. This is once again another second chance for Gawain, but also specifically in the context of his necessity to survive to fulfill his duty, providing Gawain an opportunity to fulfill his duty despite his past mistakes when hesitating to take up the Green Knight’s challenge. However, it’s also important to consider whether or not Gawain’s second chance in this case was divine intervention from his prayer to Mary, or a second chance he redeemed from his own actions. But despite the way his life was saved being uncertain, Gawain was still presented with a second chance — whether it was one he seized from his own redemption or one he prayed for, representing a second chance nonetheless. These instances of second chances and Gawain’s uncertainty about his duty and life show the complexities the poem portrays about second chances in duty. The structure of the poem also reflects these repeated trials where Gawain faces second chances, as also analysed in Derek Pearsall’s “The Structure of Sir Gawain and the Green Knight.” The four fit structure shows a section where Gawain is tested once again to face a choice he must make, until finally, in the fourth fit, he’s set to face all of his previous choices and ultimately given a second chance to live, reflecting the structural support of each second chance. (Pearsall)

The next second chance that Gawain takes is when he arrives at the Lord’s court, in the third fit. When initially meeting the Lord, the Lord proposes a game of exchange to Gawain. The poem reads:

“And Gawain,” said the good host, “agree now to this:

Whatever I win in the woods I will give you at eve,

And all you have earned, you must offer to me;

Swear now, sweet friend, to swap as I say,

Whether hands in the end be empty or better.

“By God,” said Sir Gawain. “I grant it fortwith!

If you find the game good, I shall gladly take part.” (ll. 1105 – 1110, Borroff)

This shows the Lord’s offer of a second chance, despite Gawain’s initial ignorance of the true nature of the Lord’s game. However, the Lord’s game adds complexity because it depends on one Gawain’s duty as a knight, which a lack of brought him to his death — he needs to be honest to the Lord. This is a second chance to redeem his duty to better himself from his initial mistake that led Gawain to what he perceived as his imminent death. Gawain, however, successfully engages in the exchange of winnings, taking this second chance for his life and utilizing it. The only exception in this game was the last day, when he did not give the Lord the girdle out of the desire to save his life. The girdle’s role in the games is also significant. In Jane H.M Taylor’s “The Girdle and Its Meaning in Sir Gawain and the Green Knight”, the girdle is shown to be a badge of humility, stemming from a desire to live, but eventually evolves into a partial redemption after Gawain’s mistakes and through his second chances (Taylor). Gawain’s intentions with the girdle and its representation, and Gawain’s honesty regarding the Lord’s game is an interesting juxtaposition between Gawain’s honesty and his mistakes — while he was honest and redeemed himself in his duty by being honest, the mistake he made when he was dishonest stemmed from Gawain’s desire to live. On the third day of the exchange of winnings, when Gawain is considering lying to save his life, the poem reads:

When he gains the Green Chapel to get his reward:

Could he escape unscathed, the scheme were noble!

Then he bore with her words and withstood them no more,

And she repeated her petition and pleaded anew,

And he granted it, and gladly she gave him the belt,

And besought him for her sake to conceal it well. (ll. 1857 – 1862, Borroff)

In this next passage, we can see Gawain deliberately trying to be dishonest and “conceal” what would keep him alive. While the action of Gawain preserving his life is arguably ingrained in human nature, his dishonesty still is not representative of the values that a knight upholds — a mistake in the context of his duty. This mistake is later revisited when Gawain faces the consequences of the Lord’s game. When Gawain came to the Green Chapel to face the Green Knight, who was revealed to be the Lord, he was told he would receive one hit with the axe due to lying on the third day of the Lord’s game. While receiving the stroke, however, Gawain flinches and is criticized by the Green Knight. The poem reads:

“Bestow but one stroke, and I shall stand still,”…

And his [Gawain’s] shoulders shrank a little from the sharp iron.

Abruptly the brawny man breaks off the stroke,

And then reproved with proud words that prince among knights.

“You are not Gawain the glorious,” the green man said,

“That never fell back on field in the face of the foe,

And now you flee for fear, and have felt no harm:

Such news of that knight I never heard yet!

I moved not a muscle when you made to strike” (ll. 2267 – 2274, Borroff)

This passage shows the Green Knight is directly criticizing Gawain’s bravery and courage, which is part of his duty. He denies Gawain being himself, stating that Gawain is “not Gawain the glorious” who had “never fell back on the field in the face of foe.” This is significant, as the Green Knight denying Gawain being himself and “glorious” is him denying Gawain being a good knight who never feared “in the face of foe.” The Green Knight also criticizes Gawain for being a coward, saying “now you [Gawain] flee for fear.” Here, the Green Knight is denying Gawain’s knightly qualities, essentially saying by flinching, he hasn’t been a good knight. This is especially significant considering the honor accompanying medieval knighthood, as explored by Derek Brewer’s “The Ethics of Honor in Medieval Knighthood.” The honor and duty that accompany medieval knighthood were broken by Gawain’s fear of death, as Gawain’s frailty in the face of death highlights his imperfections as a knight. (Brewer) Further, Gawain also does make a mistake prior to his action of flinching because he lies about being still but flinches anyway, saying “I shall stand still” and yet “his shoulders shrank a little from the sharp iron,” representing him making a claim of being brave and not holding himself to it — a mistake in his duty to be brave as a knight. The Green Knight feigns a second hit, in which Gawain doesn’t flinch, and on his third hit, he does not behead Gawain — only nicks him. The Green Knight explains his intentions of the hit, saying:

“I owed you a hit and

you have it; be happy therewith!

The rest of my rights here I freely resign.

Had I been a bit busier, a buffet, perhaps,

I could have dealt more directly, and done you some harm…

True men pay what they owe:

No danger then in sight.

You failed at the third throw,

So take my tap, sir knight.” (ll. 2341-2357, Borroff)

In this passage, after Gawain’s third hit is revealed to be because he lies, as the Green Knight says, “you failed at the third throw.” However, the Green Knight didn’t behead him, showing that one simple nick was enough for Gawain “pay[ing] what [he] owe[d]” and also referred to him as “true man,” implying Gawain’s honesty despite the nick being due to him lying. This implies that if he’d fully lied and been dishonest, he would have been hit thrice — one for a lie on each day — and likely killed. Gawain, in being honest in the game of winnings, had unknowingly redeemed himself from his mistake at the feast last year when attempting to cheat the game by being honest and coming to fulfill the game; he was properly fulfilling what he should be doing as a knight, other than his mistake of dishonesty, which he was punished for. Further, despite his punishment, Gawain was still given a second chance because he wasn’t killed — he still had his life to make up for the mistakes he made of lying. The Green Knight also considers the context of Gawain’s lie, saying:

“So is Gawain, in good faith, to other gay knights.

Yet you lacked, sir, a little in loyalty there,

But the cause was not cunning, nor courtship either,

But that you loved your own life; the less, then, to blame.” (ll. 2365-2368, Borroff)

Here, the Green Knight also directly addresses his dishonesty and says that, despite his dishonesty not being true to his duty as a knight, he can’t be blamed for just wanting to live. The incompatibility of these concepts is also explored in Jesse Roberts’s “Chivalric Duty and Human Fallibility”. Both the honors of knighthood and Gawain’s methodology of preserving his life and his own human fallibility force Gawain to address the tension between these two values. (Roberts) This represents a more nuanced view of Gawain’s lie, building on the portrayal of life and duty in the poem. Despite his duty, Gawain had prioritized his life over upholding the values of his duty. Even then, he is still constantly faced by the weight of his mistakes, but at the same time, given constant second chances to improve and redeem himself. The nick he got for his dishonesty is a final representation of that second chance, and how life ties into duty — he was given a final second chance to live and uphold his duty after learning from the several mistakes he made. Gawain addresses this, saying:

“Your cut taught me cowardice, care for my life,

And coveting came after, contrary both

To largesse and loyalty belonging to knights.” (ll. 2379 – 2381, Borroff)

Gawain directly says he learned more about the duty that belongs to knights by saying the Green Knight “taught [him] cowardice…and loyalty belonging to knights” telling us that his experience prior to the games was lacking but he learned from the entire ordeal with the Green Knight. This shows that his redemption did affect the way he viewed his duty as a knight, and now he has a better view of how to “Care for [his] life” along with harnessing the loyalty belonging to knights. This change in Gawain is also shown in the way the poem describes him. It reads:

Wild ways in the world our worthy knight rides

On Gringolet, that by grace had been granted his life.

He harbored often in houses, and often abroad,

And with many valiant adventures verily he met…

The nick on his neck he naked displayed

That he got in his disgrace at the Green Knight’s hands…

“For where a fault is made fast, it is fixed evermore…” (ll. 2479-2512, Borroff)

Gawain is directly described to be “a worthy knight,” which shows that he is now truly a knight following his duty, and directly addresses his mistake and how it is now “fixed evermore.” His opportunity for this was only possible because of the second chance to live from his duty he got from the exchange game, showing that the message portrayed in Gawain’s character is that redemption in duty is achieved through second chances despite mistakes and mishaps made throughout your life. He did not portray perfection in his duty, but instead had a balance between redemption in his duty and consequences — something that the nick on his neck represents. He did not redeem himself fully, but his partial redemption allowed him to learn from the past mistakes he had made within his duty.

Throughout Sir Gawain and the Green Knight, there is a repetitive and continuous pattern of making mistakes within one’s duty and redeeming oneself. Zooming out, the portrayal of the character Gawain — who is highly praised for being a compassionate and chivalrous knight — openly making mistakes, is unorthodox. These ideas of Gawain as a perfect knight are explored in Kennis Jobe’s “A Model Knight: Sir Gawain, Chivalric Contradictions, and Grief in Medieval Literature.” This different portrayal of him is significant, considering Gawain’s previous portrayal as a model knight in previous works featuring Gawain, such as L’arte Périlleux and Claris et Laris. (Jobe) However, the appeal in a story like this shows in its message of redeeming oneself within duty. It has a certain ignorance toward the concept of perfection at duty and embraces the priority of your life and humanity in the actions of constant improvement, despite past portrayal as a model knight. Ultimately, this poem makes a powerful statement on the complexities of the relationship between life and duty, illustrating a message that, despite the weight of expectations and the want of perfection, the honest way to be true to one’s duty is achieved through constant improvement from past mistakes and seizing second chances to be better.

Works Cited

Borroff, Marie, and Laura L. Howes. Sir Gawain and the Green Knight: An Authoritative Translation, Contexts, Criticism. W. W. Norton & Company, 2022.

Pearsall, Derek. “The Structure of Sir Gawain and the Green Knight.” Speculum, vol. 52, no. 4, 1977, pp. 619–640.

Gusdorf, Georges. “The Game of Chance: Moral Ambiguity in Sir Gawain and the Green Knight.” Modern Philology, vol. 83, no. 1, 1985, pp. 67–78.

Brewer, Derek. “The Ethics of Honor in Medieval Knighthood.” Journal of Medieval History, vol. 14, no. 1, 1988, pp. 39–48.

Jobe, Kennis. “A Model Knight: Sir Gawain, Chivalric Contradictions, and Grief in Medieval Literature.” 2023. Louisiana Tech University, Louisiana Tech Digital Commons, https://digitalcommons.latech.edu/cgi/viewcontent.cgi?article=1104&context=theses

Nicolson, Marjorie. “Second Chances and Self-Knowledge in Sir Gawain and the Green Knight.” Studies in Philology, vol. 82, no. 3, 1985, pp. 281–294.

Taylor, Jane H.M. “The Girdle and Its Meaning in Sir Gawain and the Green Knight.” The Review of English Studies, vol. 56, no. 225, 2005, pp. 362–374.

Roberts, Jesse. “Chivalric Duty and Human Fallibility.” Speculum, vol. 70, no. 4, 1995, pp. 797–820.

About the author

Ananya Kota

Ananya Kota is an 11th grader at Los Altos High School. She interns at her local newspaper as a reporter and is a community editor for her local student-run journalism publication. She is a peer tutor at her school and is the co-founder of a local youth lit-mag.

The post Second chances and Redemption in Sir Gawain and the Green Knight appeared first on Exploratio Journal.

This paper examines the stability of five leading stablecoins USDT, USDC, BUSD, TUSD, and DAI using a nonlinear machine learning model combined with an event based analysis of major depegging episodes. Fiat backed stablecoins show muted and short lived deviations from their pegs during external shocks, reflecting liquid reserves, arbitrage and institutional support, and often trade at small premiums. By contrast, the crypto collateralized DAI comoves strongly with systemic risk, embedding mark to market leverage, on chain frictions and liquidation dynamics that mirror contagion effects in the banking literature. Our approach validates and extends recent work on stablecoin fragility and shows how design choices translate into distinct patterns of resilience or vulnerability under stress, with implications for regulation and digital asset market structure.

1. Introduction

When Silicon Valley Bank collapsed in March 2023 it sent a shockwave through the stablecoin market. The news that Circle held part of USDC’s reserves at the failed bank drove its price down to about $0.87. DAI, which is backed by crypto collateral, also slipped below its peg. This episode, together with earlier events such as the 2018 USDT reserve rumor discount and the 2020 Black Thursday crisis in DAI, highlights a fundamental divide in how different types of stablecoins behave under stress.

Fiat backed stablecoins such as USDC, USDT, BUSD and TUSD mainly face redemption bottlenecks during moments of panic. Because their backing sits in cash or liquid assets, arbitrage and institutional support usually close the gap quickly, and these coins often trade at a small premium rather than a discount during calm periods. By contrast, crypto collateralized coins such as DAI embed mark to market leverage, liquidation risk and on chain frictions directly into their design. When the underlying collateral becomes volatile or gas fees spike, liquidations cascade, arbitrage slows, and prices can swing both below and above the peg. This reflects the panic-driven withdrawals and cascading effects described in Diamond and Dybvig’s model of bank runs.

In Section 1, the analysis introduces the contrasting behavior of fiat-backed and crypto-collateralized stablecoins under stress, using the USDC–SVB banking shock, the 2018 USDT reserve-rumor episode, and Black Thursday (2020) to illustrate why collateral design and on-chain frictions matter. Section 2 reviews the existing literature on stablecoin stability, systemic risk transmission, and nonlinear modeling, drawing on the work of Lyons and Viswanath-Natraj, Grobys et al., and Klages-Mundt et al. Section 3 outlines the data and methodology, combining a Gaussian Ridge Neural Network estimation of daily stablecoin prices against four macro-financial risk indexes with a structured event analysis of major depegging episodes between 2018 and 2024. Section 4 reports the main results, showing that fiat-backed stablecoins exhibit low SSE and weak correlations with systemic risk, whereas DAI shows high correlation and mixed-sign coefficients. Model predictions are compared with real-world events to demonstrate that macro shocks affect fiat-backed coins briefly, while on-chain shocks cause deeper, asymmetric deviations in DAI. Finally, Section 5 discusses the implications for stablecoin design, financial stability, and the regulation of crypto-dollar instruments.

2. Literature Review

  Stablecoins resemble fixed exchange rate regimes because they promise convertibility at par, yet their credibility depends on collateral, redemption, and confidence. Lyons and Viswanath-Natraj (2023) show that fiat backed designs such as USDT and USDC remain close to par through arbitrage and redemption and often trade at small premiums. Grobys et al. (2021) document that crypto collateralized tokens such as DAI display nonlinear dependence on systemic risk indexes. These findings echo Diamond and Dybvig (1983), where stability is sustainable in good states but fragile when coordination failures and run dynamics emerge.

  A second group of studies focuses on how stablecoin designs embed different risk channels. Klages-Mundt et al. (2020) classify stablecoins into fiat backed, crypto collateralized, and algorithmic types and show that risk profiles vary sharply across designs. Crypto collateralized coins encode mark to market leverage, on chain liquidation risk, and settlement frictions. Algorithmic designs attempt to engineer stability reflexively but can amplify feedback loops. The Terra Luna collapse in 2022 confirmed these theoretical warnings, while the USDC–SVB banking shock showed that even fiat backed coins can temporarily lose their peg. Liquidity concentration on venues such as Curve 3pool and Binance has also shown that market microstructure can transmit stress (Briola and coauthors, 2023).

  A third group of studies applies advances in financial econometrics and machine learning. Mallqui and Fernandes (2019) and Shen et al. (2020) show that radial basis function neural networks outperform linear benchmarks in predicting asset prices and volatility. Corbet et al. (2021) survey machine learning applications in crypto markets and find that neural and recurrent architectures can identify volatility patterns that GARCH style methods may miss.

  This paper extends the literature by applying a radial basis function neural network to five leading stablecoins (USDC, USDT, BUSD, TUSD, and DAI) and linking daily prices to four macro financial risk factors. By evaluating both the sum of squared errors and the correlation between predicted and observed series, the analysis captures predictive accuracy and structural co movement with systemic risk. Combining model-based results with event-based evidence from major depegging episodes shows that fiat backed coins mostly experience short lived redemption pressures, while crypto collateralized coins encode collateral volatility and on chain frictions.

 3. Data and Methodology

This study employs a dual-method approach to examine stablecoin stability. On the quantitative side, the analysis constructs and trains a Gaussian Ridge Neural Network (GRNN) to model nonlinear sensitivity of stablecoin prices to macro-financial risk indexes. On the qualitative side, structured event observation complements the quantitative modeling.

It is important to note that the sample ranges differ across stablecoins, reflecting their varied launch dates. As a result, correlation estimates are not strictly apples-to-apples. For example, USDT and DAI have longer and more volatile histories than newer entrants such as BUSD and TUSD. This difference in data coverage should be taken into account when interpreting the comparative strength of correlations across stablecoins.

A. Quantitative framework

The quantitative analysis uses a Gaussian Ridge Neural Network (GRNN) to link stablecoin price with systemic financial risk indexes. Gaussian ridge functions capture the nonlinear behavior typical of stablecoins, which remain close to their peg under normal conditions but deviate sharply during systemic or crypto-specific stress. This design enables the model to detect nonlinear fragility that linear regressions fail to capture. The model uses daily values of four macro-financial indexes—NFCIRISK, KCFSI, STLFSI4, and the 10-Year Expected Inflation Risk Premium—from the Federal Reserve’s FRED database and use them as the feature vector (the model’s inputs).

The model estimates relationships between daily stablecoin prices to four macro-financial risk factors. Let

Each stablecoin (USDT, USDC, DAI, BUSD, and TUSD) is estimated independently using identical macro financial inputs and two hidden nodes. The model optimizes weights, centers, spreads, and biases by minimizing the sum of squared errors (SSE) between observed and predicted prices.

Step 1: Input Layer to Hidden Nodes (Linear Stage). For each hidden node j ∈ {1, 2}, the model computes a separate weighted sum of the four macro- financial risk factors plus a bias term:

Step 2: Hidden Node Activation (Nonlinear Stage). ach hidden node transforms its input through a Gaussian ridge function:

Step 3: Output Layer (Linear Stage). The hidden node activations are combined to generate the predicted price (or deviation from par) of the stablecoin:

where β₀is the output bias and v₁, v₂ are weights from hidden nodes to the output node.

Step 4: Error. The model’s error term for each observation is the difference between the predicted and actual price:

where y_t is the observed stablecoin price.

Step 5: Model Fit. The model measures overall fit using the Sum of Squared Errors (SSE):

and by the Pearson correlation coefficient between actual and predicted prices:

As shown in Figure 1, the network links four macro-financial risk factors to two hidden nodes and then to an output node representing the predicted stablecoin price or deviation from par.

B. Event Observation Framework

The analysis compiles a structured dataset of major stablecoin depegging episodes between 2018 and 2024 to complement the model-based analysis. For each event, the event window and the date of maximum deviation, the affected stablecoin or coins, the lowest observed price recorded on CoinMarketCap during the episode, and a classification of the primary trigger are documented. The analysis codes triggers as either macro-financial such as external banking shocks, market stress, or regulatory actions or on-chain/DeFi, including protocol-specific failures, liquidity imbalances, or infrastructure stress. This classification enables us to distinguish between stress transmitted through traditional financial channels and stress that originates within digital-asset markets.

The analysis draws events from multiple sources including industry reports, regulatory filings, market data providers such as DeFiLlama and Kaiko, and commentary from central banks. The framework organizes each episode into six thematic drivers of fragility: market stress and panic events, regulatory and legal drivers, blockchain and infrastructure dependence, issuer behavior and transparency, liquidity concentration and market microstructure, and adoption or utility shocks.

  This event-based framework captures dimensions of fragility, confidence, governance, and infrastructure bottlenecks that lie outside the scope of purely statistical modeling. Together with the GRNN estimation, it provides a more holistic view of stablecoin stability, linking sensitivity to systemic risk factors with the historical record of crises and structural vulnerabilities.

4.  Analysis Results

A. Quantitative Results: Stablecoin Sensitivity to Financial Risk Indexes (GRNN)

After minimizing SSE, the estimated input-to-hidden weights show a sharp contrast between fiat backed and crypto collateralized stablecoins. Fiat backed coinsload near one across systemic risk indexes, consistent with a muted and proportional response to macro conditions. By contrast, DAI exhibits large mixed-sign coefficients and a high bias term.

  Figure 2 plots SSE against correlation for the five stablecoins, illustrating how DAI diverges from the fiat backed group. Figure 3 shows the average absolute input-to-hidden weights by risk factor and stablecoin, highlighting the near-unit values of fiat coins and the much larger magnitudes of DAI.

The large mixed sign coefficients for DAI provide evidence that leverage and on chain frictions transmit macro shocks directly into the stablecoin’s peg. Fiat backed stablecoins work much like a currency board or a hard peg regime: they hold reserves in cash or short term government securities and can meet redemptions quickly, which limits how far prices move when stress hits. Crypto collateralized coins such as DAI are closer to a soft peg backed by volatile assets.

Because DAI’s collateral is marked to market on chain, any rise in systemic risk immediately cuts collateral values and pushes collateral ratios toward liquidation. This sets off margin calls, liquidations, and delays in arbitrage that make price swings larger and longer. On chain bottlenecks such as gas fee spikes or thin liquidity slow down adjustment further and create the kind of liquidity spirals seen in past financial crises. The large mixed sign coefficients estimated for DAI are not random noise but evidence that leverage and on chain frictions transmit macro shocks directly into the stablecoin’s peg.

B. Event Observations: Linking Model Predictions to Real World Stress Episodes

A structured dataset of major depegging episodes between 2018 and 2024 was compiled, recording for each episode the event window, affected stablecoins, lowest observed price on CoinMarketCap, and the primary trigger categorized as either macro-financial or on-chain/DeFi. Table 1 summarizes these events. Macro events such as the SVB banking shock and BUSD’s regulatory action caused temporary but pronounced deviations in fiat backed coins. On-chain events such as Black Thursday (2020) and Curve 3pool imbalances (2023) produced sharper and more asymmetric deviations in DAI and USDT. Comparing GRNN predictions with observed prices shows that the model captures macro-financial sensitivity but underestimates DeFi-specific shocks, consistent with its input structure based on four systemic risk indexes.

 TABLE 1—MAJOR STABLECOIN DEPEGGING EPISODES, 2018–2024

Figure 4, Figure 5 and Figure 6 compare DAI price behavior with Ethereum market conditions in March 2020.

 The first figure plots daily DAI deviations from one dollar together with the Ethereum average gas price. Deviations rise when gas fees are elevated, which suggests that network congestion makes it harder to execute arbitrage or liquidations that would normally stabilize the peg. The second figure contrasts DAI daily highs and lows with the Ethereum low price over the same dates. Around mid-March, when Ethereum volatility jumps, the DAI high low spread widens at the same time, which points to stress in collateral mechanics and liquidity. Importantly, DAI moved both above and below one dollar. It fell below par when confidence weakened after collateral auctions failed to clear, and it rose above par when liquidators and arbitrageurs needed DAI to repay vault debt, which created temporary scarcity. Taken together, the patterns indicate that DAI instability during stress reflects not only broader market shocks but also on chain frictions such as high gas costs and collateral volatility.

Figure 5. Ethereum Average Gas Price in March 2020

5. Conclusion

This paper analyzes the stability of leading stablecoins using a nonlinear machine learning model combined with a review of major depegging episodes. The results reveal a clear divide between fiat backed and crypto collateralized designs. Fiat backed stablecoins show muted and short lived deviations from their pegs during external shocks, reflecting liquid reserves, arbitrage and institutional support. In contrast, the crypto collateralized DAI moves more strongly with systemic risk, embedding mark to market leverage, on chain frictions and liquidation dynamics similar to run effects in traditional finance. Linking model based evidence to historical stress events validates and extends recent work on stablecoin fragility, showing that fiat backed coins behave like tightly managed exchange rate regimes, while crypto collateralized coins resemble leveraged intermediaries whose stability depends on collateral valuation, market infrastructure and the speed of on chain adjustments. Future research could integrate real time indicators of liquidity and collateral quality, examine the market microstructure of trading venues and bridges, and test policy or design interventions such as redemption limits or insurance funds to better assess stablecoin resilience under stress.

References

Briola, Riccardo, and coauthors. 2023. “Anatomy of a Stablecoin Run: Evidence from the Terra-Luna Collapse.” Finance Research Letters, 51: 1544–6123.

Corbet, Shaen, Brian Lucey, Larisa Yarovaya, et al. 2021. “Machine Learning in Cryptocurrency Markets: A Survey.” Finance Research Letters.

Diamond, Douglas W., and Philip H. Dybvig. 1983. “Bank Runs, Deposit Insurance, and Liquidity.” Journal of Political Economy, 91(3): 401–419.

Grobys, Klaus, et al. 2021. “Stablecoins and Systemic Risk: Nonlinear Dependence and Stress Episodes.” Finance Research Letters.

Klages-Mundt, Ariah, Dominik Harz, Lewis Gudgeon, Jun-You Liu, and Andreea Minca. 2020. “Stablecoins 2.0: Economic Foundations and Risk-based Models.” AFT ’20, 59–79. ACM.

Lyons, Richard K., and Ganesh Viswanath-Natraj. 2023. “What Keeps Stablecoins Stable?” Journal of International Money and Finance, 131: 102838.

Mallqui, Daniela C., and Ricardo A. Fernandes. 2019. “Predicting the Direction, Maximum, Minimum, and Close Values of Daily Bitcoin Price Using Machine Learning Techniques.” IEEE Access, 7: 148551–148563.

Shen, Dawei, et al. 2020. “Nonlinear and Deep Learning Approaches to Crypto Asset Volatility Forecasting.” Applied Soft Computing.

About the author

Abhiram Kode

Abhiram is a rising 11th-grade student at Rock Hill High School in Frisco, Texas, with strong academic and research interests at the intersection of finance, technology, and engineering. He is deeply passionate about investment banking, fintech, cryptocurrency markets, and applied robotics, and actively pursues opportunities that blend analytical thinking with real-world problem solving.

Beyond research, Abhiram tutors mathematics at Kumon, plays varsity tennis, and participates in competitive chess and speed cubing. He has earned multiple national and international awards in mathematics and science Olympiads. Known for his curiosity, discipline, and self-driven learning, Abhiram aspires to pursue a future career that combines finance, technology, and innovation.

The post Stablecoin Stability Under Stress appeared first on Exploratio Journal.

Introduction

“I was neither able to sleep, nor was I able to move out. Many don’t take these medications because of this fear only. ” This was from an unnamed 40-year-old rural male patient from Nagpur, India, who reported adverse drug effects as a barrier for treatment adherence.

“I felt like I was going up and down; I could not sleep the whole night. Taking 12-13 pills was impossible for me… I am already weak, even when you utter my name of taking medicine, my head starts cracking. ”

This was from another rural male patient, but this time 28 years of age, who also mentioned that the side effects were exacerbated due to the quantity of pills and consistency of time required to complete treatment, another key factor as to why long treatment fails.

The above quotes represent rural patients’ experiences with multidrug-resistant tuberculosis and its health effects (Deshmukh, Dhande, et. al, 2015). This came from a study between 2012 and 2013, in the Nagpur Drug Resistant TB Centre, a drug resistant tuberculosis center in India, where patients were randomly chosen to describe their feelings after an intensive drug prescription session after they had been diagnosed with multidrug-resistant tuberculosis, one of the most dangerous infectious diseases in India right now, if not the most dangerous, according to the CDC as of 2024. Patients have had difficulty adhering to treatments and consistently upholding their regimens due to many reasons; it could all be too much for them and draining their energy or they could have a mental stigma against these medications. All of these will be discussed later in the paper. But first, we must learn more about the disease of multidrug-resistant tuberculosis, which is lately causing a lot of problems for patients in India across both urban and rural settings in terms of upheavals of social dynamics and biomedical issues.

Multidrug-resistant tuberculosis (MDR-TB), or rifampicin-resistant tuberculosis (RR-TB) is a major, increasingly dangerous, and virulent infectious disease in today ’ s world. Harboring much of the same symptoms of regular tuberculosis, including fever, chest pain, general weakness, cough, and sputum production, MDR-TB is a more dangerous and form of TB, showing large amounts of resistance to major drug classes and products including rifampicin and isoniazid, both commonly used and powerful first-line drugs to treat TB that are now obsolete to treat MDR-TB. This drug resistance is, from the biomedical perspective, caused by increasing numbers of efflux pumps in MDR-TB cells that pump out antibiotic drugs intended to kill the pathogen and more enzymes that inactivate drugs like rifampicin and isoniazid. As a result, the pathogen becomes more potentially fatal considering there are less options for medical professionals to successfully treat the disease as time goes on.

Discovered in 2012 in a Mumbai hospital, the impacts of MDR-TB have gotten worse for a long period of time, mainly explained by the fact that India continues to have 26% of global TB cases as of 2023 (Mandal, Rao, Joshi, et al.). It has become a public health crisis , as this 26% involves 8.2 million people diagnosed with tuberculosis, 1.23 million of those people dying that year.

However, much of the current medical community overlooks the important sociocultural and socioeconomic factors that play a role in exacerbating the MDR-TB situation in India. In culturally-diverse areas with different ways of living and interpreting the world, disparities are bound to occur in terms of medical treatments and how the government and politicians make relevant policies or participate in corruption with regards to MDR-TB regulation and management. These disparities is a main point of focus for medical anthropologists, who use them to explore the historical, sociocultural, socioeconomic, political, economic, and biomedical discrepancies that set the stage for the current crisis of MDR-TB.

The pathogen’ s history of interventions and attempts at treatments, ranging from physical sanatoria to increasing reliance of pharmaceutical drugs after much biomedical research, paints a picture of how global research, beliefs, and actions taken to address tuberculosis has grown over time, especially considering different perspectives and treatment theories that have sprouted throughout history. In addition, socioeconomic disparities, which tend to be highlighted in a densely-populated developing country like India where even an 11.9% poverty rate (as of 2021) is large due to being the most populated nation (as of April 2023), run rampant, consisting of radical differences and discrimination in opportunities for personal and professional development between urban and rural areas (Forbes India, 2024). As will be discussed later, political pressure and corruption is also there to sometimes curb honest data and initiatives being passed, while pharmaceuticalization has grown to be an integral part of India ’ s GDP and overall economic policy.

Integral to the sociological analysis of the TB crisis is the phenomenon of medicalization, a process in which a certain health problem (whether it has to do with psychological, mental, or cultural illnesses) is transformed into a medical problem, where medication and mainstream medicine picks up treatment of this particular illness. In many cases, medicalization can be of benefit to certain sufferers; utilizing prescription drugs and treatments for psychological conditions like schizophrenia and depression has led to success in treating, controlling, and sometimes curing these illnesses. However, most cases of medicalization in other countries (especially developing countries) have actually caused more harm than benefit, often straying the focus away from the ever-important cultural and sociological impacts and influences of disease (Lantz, Goldberg, Gollust, 2023). Therefore, this paper focuses on the classic examples of medicalization in the context of tuberculosis in India, and how that has inadvertently led to its rising drug resistance.

The late sociologist Peter Conrad found that society is now witnessing the “ shifting engines of medicalization, ” explaining how the agents and factors causing medicalization are now shifting away from medical professionals to entities like the pharmaceutical and biotech industries, propelled by consumer demand and commercial influence. The boom in pharmaceutical drugs and treatments via the multiple microbusinesses and private local health practitioners, providing the bulk of Indian healthcare, add further fuel to current medicalization and drug resistance.

This recent emphasis on medicalization also brings forth another aspect into the issue: sociocultural factors. A culturally rich and diverse nation like India harbors multiple cultural beliefs, customs, and practices relating to the health of their various regional populations. Regional cultures, before the arrival of modern medicine and thought, have tended to view disease, especially tuberculosis, in ways that focused more on the social determinants of health rather than the biomedical ones. As we have seen modern medicine and the current global public health system essentially flip the script on this initial approach, community interactions between the old and new will be integral to developing and understanding holistic approaches towards tackling disease.

Historical

Tuberculosis, let alone MDR-TB, has had a long, complex history. Formally discovered in 1882 by Dr. Robert Koch, tuberculosis had been killing “ one in every seven people in the United States and Europe [at the time], ” according to the CDC. However, TB has existed for thousands of years, even showing up in India through ancient medical records and artifacts. During the early 1900s, India largely used sanatoria (isolated medical facilities focusing on good hygiene and care barring antibiotics) to treat tuberculosis, with varying degrees of success. In 1917, the first TB dispensary–a hub for testing and TB treatment–was opened in Bombay, while the first official national study on TB was conducted in 1914 by Arthur Lankester (Central TB Division, 2025 ).

The introduction of allopathic medicine from Europe to colonized nations like India initiated a focus among doctors in India on the biomedical theories and findings of Dr. Koch. Nevertheless, there were a few dissenters who were more keen in delving into alternative theories about the true causes of tuberculosis.

One of these dissenters was David Chowry-Muthu, a T amil Christian doctor specializing in TB. Apart from setting up the first sanatorium hospital in India in 1928, he is also known for challenging the then-largely-accepted bacterial theory of disease causation to instead emphasize the role of environmental factors like poor living conditions and personal well-being in the reduction of illness while avoiding the excessive inclusion of antibiotics. He outlined this stance in his 1921 book Pulmonary Tuberculosis: Its Etiology and Treatment, also proposing reductions in military expenditures to prevent war-related illnesses and investment in urban planning, economic reforms, and improvement in living standards. Even prominent Indian leaders like Jawaharlal Nehru (the first Prime Minister of India) and Mahatma Gandhi (who spearheaded the Indian independence movement), concurred, discussing environmental factors and familial experiences with TB that supported Chowry-Muthu ’ s theory; Nehru used his experience of his wife ’ s struggle with TB to stress the need for more adequate hospital resources while Gandhi emphasized public health and environmental factors like water and air quality, cleanliness, and sanitation as key players in reducing TB’ s spread.

However, Chowry-Muthu ’ s claims could not gain traction mainly due to the Madras Study done in 1950. This study demonstrated that home-based antibiotic treatment was effective in managing TB. It also initiated a rise in randomized controlled trials (RCTs) as a gold standard to determine treatment efficacy, leading to more critical views of prior treatment methods.

This larger emphasis on patient autonomy in health and medication decisions synthesized the foundation for the current state of the Indian pharmaceutical industry, which controls the means of production, ownership, and transfer of drugs and treatments for prominent diseases in India. This also includes tuberculosis, and the increasing emphasis on stronger antibiotic drug regimens. It also led to the emergence of the TB Association of India in 1939, and later the National TB Control Programme in 1962-1963 (now the Revised National TB Control Program to address disparities and deficiencies in the original program).

However, this social and medical shift also spelled problems for the control of TB in India. It opened the possibilities for usual patient non-adherence to treatments (due to indiscipline or insufficient resources and education), drug resistance, and major anxiety about the recency of treatments and their efficacies. The initially popular Bacillus-Calmette-Guerin vaccine for TB became ineffective in 1979, while the spread of human immunodeficiency virus (HIV) in India in 1984 and development of drug resistant strains of TB in 1992 spelled further trouble for those suffering from TB symptoms.These expose the deep sociocultural barriers and disparities present in various Indian communities, which exacerbate the toll TB is taking on the Indian populace with regards to the rampant antimicrobial resistance.

Sociocultural

Arguably the largest factor about the current spread of MDR-TB in India is the influence of sociocultural factors. This is true to a capacity for essentially any disease, but this has been recognized by the current medical community mainly for diseases relating to mental health and wellness, while these same factors that apply to infectious diseases with physical symptoms have been overlooked by much of this mainstream medical community, which tends to focus mostly on the biomedical aspect of these diseases. In the case of tuberculosis, even with all of its physical symptoms like coughing, sputum production, and fatigue, there are extensive cultural habits, beliefs, and practices especially prevalent in India that can be attributed to the exacerbation of certain virulence factors and creating perfect environments for maximum infection and worsening of symptoms.

The rampant medicalization in the modern world, comprised of larger focuses on biomedical aspects without consideration of sociocultural, economic, and other external factors, has led to large cultural shifts in India especially, with more urban participation in biomedical treatment regimens like Direct Observation Therapy, Short-Course (DOTS) being a largely popular treatment option. This treatment option involves regular supervision of TB patients from medical professionals (mainly to ensure treatment adherence) as they take complex doses of specific medications as a multidrug treatment, common among patients whose TB strains have gained resistance. The degree to which these kinds of programs succeed in India vary strongly by unique state funding and political support, but over the years, DOTS has become the main option for a lot of Indian citizens, with over 12 million TB patients using DOTS since the program’ s inception. However, to understand the true sociocultural and anthropological concepts underlying these issues, we need to go over some basic theories.

The concepts of illness and disease, while sounding similar, are defined differently in the medical anthropology field. Illness describes a patient’ s sociocultural experience of disrupted health, characterized by physical symptoms (like a fever or sore throat), or psychological symptoms (like missing out on a vacation with friends), meaning that illnesses are not confined in only the mental, psychological, or physical space. For example, the flu, a disease caused by the influenza virus, portrays these same aspects; an affected individual has physical symptoms like cold and runny nose as well as psychological and mental symptoms like intrinsic feeling of weariness separate from the physical malaise that the flu is known to cause. However, disease is confined to only physical illnesses and biological abnormalities, like a viral infection. It is the illness which can validly have real consequences and effects on both social dynamics and biological health, while the term “disease ” can really only be utilized to describe an ailment with physical symptoms. It is the misuse and misinformation, along with potential for social manipulation, of the definitions of these two terms that set the foundation for the underlying sociological dynamics surrounding India ’ s public health and tuberculosis situation.

Especially in the case of India, social norms and cultural practices often exacerbate and amplify this stigma and these negative social dynamics. In multiple communities, cultural dynamics and disparities continue to alienate TB patients even with current efforts by the government to reduce the incidence of TB. While the government may be dealing with the physical, biological problem of tuberculosis, not much is being done to address its persistent social impacts. Cultural beliefs and practices of citizens

According to a health care providers handbook developed by the Montgomery County Office of Community Partnerships and the Asian Pacific American Advisory Group in Montgomery County, Maryland, multiple considerations into religious, cultural, and ethnic beliefs must be taken in healthcare settings. Some cultural beliefs listed include a steadfast belief in cleanliness and bathing, higher power granted to elders of families for decision-making, occasional reliance on traditional home remedies based in Ayurvedic medicine, and a severe aversion to cow and pig materials due to religious reasons.

Though this pamphlet describes appropriate treatment strategies and ways to approach the health of Hindu patients, this applies fairly well to Indian Hindu citizens due to having the same foundational beliefs, practices, and worldviews (Queensland Health Multicultural Services, 2011). However, whatever is identical in theory may not be identical in social and physical symptoms. Some of these beliefs, including this belief in cleanliness, may not be able to be fully carried out due to inherent vulnerabilities in India surrounding unclean facilities and resources that may make it theoretically impossible to fulfill these things. In many rural communities, taking a bath may constitute bathing and submerging oneself in a holy river or nearby lake, but many of these communities may have unclean water and unsanitary facilities for this activity, resulting in inadvertent bodily contamination in the guise of an important cultural practice and belief in cleanliness.

Ayurvedic medicine, the main native-Indian medical and cultural belief and practice system based on Hindu tenets, is centered around natural materials like herbs, spices, and other plants typically found in South Asian regions, is not a proven legitimate alternative to allopathic medicine, though it shows much promise nonetheless. Due to the uncertainty of value and effectiveness of this medicine, Indian patients, especially older ones, may have a natural preference for Ayurvedic medicine, which could have an impact on the effectiveness of their treatment (if they do ultimately opt for Ayurvedic medicine), or have a psychological impact on the manner in which they utilize allopathic medicine (since they may not fully believe in it).

Most importantly, most Hindu patients view all illnesses as containing a biological, psychological, and spiritual element, often attaching a stigma to mental illness and cognitive dysfunction in particular.

This stigma results in illnesses being considered as karma for misdeeds in a past life, along with the concept of the evil eye (which is usually attributed to being a cause of mental or physical illness). These kinds of stigmas, especially amplified in rural communities, often lead to social ostracization from friend groups and extended families, which can lead to isolation and a real belief of being punished by a religious power.

The nuance doesn’t stop there. While a lack of emphasis on biomedical knowledge could definitely end up badly with social ostracization, medicalization can shake up the entire dynamic. This time, because an illness is related to an actual explainable biological problem, people tend to start avoiding affected individuals and refuse to reach out for social connections or social gathering to help accommodate the individual in the community; essentially, it is an internal exile from society that occurs.

These social conditions and issues are further exacerbated through the specific social dynamics present in care centers and hospitals in both rural and urban India. In fact, doctor-patient dynamics aren’t instrumental to just Indian TB, but to any health condition in any country. And it’ s been mainly due to American medical influence.

For example, Ethan Watters, through his New York Times article The Americanization of Mental Illness, talked about Dr. Sing Lee, a Hong Kong doctor who witnessed the moment when anorexia hit China; before the Western media could describe it, Chinese locals believed that anorexia, like multiple other physical diseases, wasn’t really connected to fat phobia, and not many reports of fat phobia came out initially (Watters, 2010). However, once the local Hong Kong population Western media connected anorexia to fat phobia, the number of reports on fat phobia in Hong Kong skyrocketed (not because there was fat phobia in the first place, but because the perception of individuals ’ health changed due to exertion of social control by the Western media).

This Americanization of illness in general continues to affect Indian tuberculosis, especially through doctor interactions. When an Indian patient visits a doctor from a high-profile medical institute or hospital, the expectation is that prescription medication and biomedical treatments will be given, due to recent Westernization of global medicine. However, the same is not true as to when a patient visits a local clinic or uncertified care provider like a Ayurvedic medicine guru in villages; in this case, patients usually expect local, homely treatments like simple spices, herbs, fruits and vegetables, and more ordinary forms of medicine rather than prescription medication.

The differences don’t stop there. The social dynamics run so deep that even the expectations for quality of care are influenced across backgrounds. Patients may expect allopathic medicine doctors from wealthier, more well-organized areas to be of higher quality, while they may also expect local healers to have less quality health (though they may go to the healer aware of this and ready to take the risk unless they truly believe in alternative forms of medicine). This just goes to show the extent to which the Western world has influenced medicine in India, and it’ s impacting tuberculosis very much.

Often with diseases like tuberculosis, mortality statistics are assumed to be directly related to medical measures and advancements directly taken by national governments to decrease incidence of a particular disease or illness. However, this is not always the case. Around the twentieth century, there was a growing discussion in the scientific community regarding the questionable contribution of medical measures and medical service expansions to a recent decline in mortality rates; this was especially seen with the decline of smallpox in Britain, with people believing that the invention of smallpox inoculation helped eradicate it. While the smallpox inoculation did play a large role in curbing smallpox cases, improvements in environment were also pointed out, mainly by Habakkuk and McKeown, especially focusing on rising standards of living (mainly in diet), hygiene improvements, and a favorable trend in the relationship between microorganisms and their human hosts.

Since 75% of the decline in mortality rates in the 20th century were associated with infectious diseases, there can be three primary influences: medical measures and immunization, reduced exposure, and improved nutrition. In the graph below (citation: McKinlay), this effect has been largely shown between men and women in the US.

Source: Medical Measures and the Decline of Mortality (McKinlay, 2013)

In addition, most of the mortality decline is from a decline in infectious diseases, so medical measures have usually been focused on this instead of other causes of mortality like heart disease, cancer, and other conditions. This further reinforces the fact that medication and biomedical advancements weren’t the chief agents that caused the massive drop in reduction in the 20th century. Especially as can be seen with tuberculosis in the graphs shown below for the nine most common infectious diseases, the first powerful and reliable drug for tuberculosis, isoniazid, came out around 1950, but the mortality rate associated with TB was already decreasing significantly by that time (McKinlay, 2013).

Source: Medical Measures and the Decline of Mortality (McKinlay, 2013)

So because these medical measures contributed little to the overall decline in mortality for the US, this data can be extrapolated and generalized for tuberculosis in India as well. There is, in reality, a much larger emphasis on cultural contexts, practices, and beliefs through this concept than biomedical interventions when it comes to tuberculosis rates in India. Therefore, medicalization, by amplifying the need to focus on the biomedical aspect, is indirectly hurting efforts to control tuberculosis long-term while risking to increase resistance to dangerous levels.

This rampant medicalization in the modern world has led to large cultural shifts in India especially, with more urban participation in biomedical treatment regimens like Direct Observation Therapy, Short-Course (DOTS) being a largely popular treatment option, involving regular supervision of TB patients from medical professionals to ensure treatment adherence. The degree to which these kinds of programs succeed in India vary strongly by unique state funding and political support, but over the years, DOTS has become the main option for a lot of Indian citizens, with over 12 million TB patients using DOTS since the program’ s inception.

DOTS has a lot of social nuances to it. The concept, involving supervision and encouragement from medical professionals to take large, consistent regimens of medication to fight TB (the prescriptions grow larger as TB becomes more resistant), may seem theoretically sound, but practically, it’ s more complicated than that. The main complaint with DOTS has been the social connection between the medical provider and patient. If the medical provider is a distinguished health professional or doctor while the patient is a rural patient, there may not be much trust and connection immediately that may guarantee a consistent adherence to the treatment regimen. However, a local healer facilitating the DOTS process may have much more success due to greater familiarity and connection and trust. This, as will be discussed later, can only be achieved through regulation of the private sector, which has so far been a huge missed opportunity for the Indian government.

Socioeconomic and political economy

Just as there are sociocultural disparities and nuances with the way healthcare resources are utilized for tuberculosis treatment, socioeconomic gaps and political influence reign supreme in determining the way the Indian public health system deals with MDR-TB. However, some major economic drivers and players need to be examined to first get a grasp on the scope of the issue at hand.

As discussed earlier, the newfound citizen medical and health autonomy has come in recent times with a stronger pharmaceutical sector. The Indian pharmaceutical sector is one of the most popular and sought-after markets in the world, and it’ s very easy to see why it’ s called the “Pharmacy of the World” . With over 10,500 manufacturing facilities, this sector, the 3rd largest (by volume) and 14th largest (by value) global provider of generic drugs, is mainly used for aspects of global medicine like affordable vaccines and treatments; this has been so well done that India is known for giving low-cost, high-quality medicines to its citizens and to other countries receiving Indian imports. This cost efficiency and innovation has greatly enhanced India ’ s GDP and improved healthcare outcomes for diseases like tuberculosis.

According to the Indian Brand Equity Foundation (IBEF), as of 2024, the Indian pharmaceutical market was worth 65 billion USD and is expected to reach a valuation of 130 billion USD by 2030 and a valuation of 450 billion USD by 2047. In addition, India has the largest number of USFDA-compliant pharmaceutical plants outside the US, along with over 2,000 World Health Organization Good Manufacturing Practices (WHO-GMP) approved facilities with more than 10,500 facilities in more than 150 countries. These statistics continue to show the sheer dominance, reliability, and influence India holds in the global pharmaceutical market. This ultimately has many effects towards the national economy.

According to the International Monetary Fund (IMF) DataMapper and other recent data from the Indian government, the Drugs and Pharmaceuticals Industry has a large 1.72% contribution to the national GDP (Make in India, 2025). In addition, a trade surplus (meaning more pharmaceutical goods have been exported rather than imported, which increases GDP contribution) has also been maintained since 2010, with an annual trade surplus of about $13.10 billion USD in the 2018-2019 year range. The industry has also received a cumulative FDI (foreign direct investment) of about $16.5 billion USD from April 2000 to March 2020, showing its appeal and potential for further outside investment. Distribution of drugs via the pharmaceutical sector is achieved through multiple health care centers and health-based microbusinesses, mainly prevalent in multiple population-dense areas and making up nearly 30% of India ’ s GDP (Aftab, 2024).

The scope and grandeur of the Indian pharmaceutical industry has so far been conveyed with the above economic statistics and information. However, with a densely populated country like India, problems and socioeconomic disparities are bound to occur with how the pharmaceutical sector transfers and communicates health information and medication to the public, with both urban and rural areas having numerous issues regarding this.

When it comes to the quality of healers, it was already mentioned earlier that perceived higher quality healers, which tend to be more professional healthcare providers from the biomedical sector, are seen more favorably by the expectations of patients than perceived lower quality local healers. In addition to this, as may be obvious, these higher quality healers tend to be more expensive and may be inaccessible to poorer individuals (of which there are many in rural areas), while lower quality healers may be the first choice due to cost efficiency. However, this relationship between quality of care and socioeconomic standing greatly widens the wealth and health gap, as poorer individuals tend to have worse health outcomes with TB than wealthy individuals, all because of class differences between local healers and more high-profile health professionals in relatively large hospitals.

This can also be seen with DOTS, as it was already mentioned earlier that DOTS tends to be more successful if trust and connection is there between patient and health provider; this tends to be truer if a wealthy patient connects with a health professional while a poor patient might connect better with a local healer (again, there will be a difference in quality of care if this occurs, and it may not look good). Therefore, it can be said that higher quality DOTS is more available and viable to individuals in high socioeconomic standing and quality of living, while the opposite is true for lower socioeconomic standing, which may not get proper DOTS treatment from local healers, especially considering the lack of governmental regulation of the private sector of health.

The simple solution to this, one could say, is to meaningfully expand higher quality DOTS care, medication, and health resources to poorer parts of the country. However, an expansion of care, testing units and areas, treatments, and appropriate medical expertise to more rural areas of India while keeping consistency of good quality is incredibly difficult and costly; this is especially true for India, the world’ s most populated nation. Costs for the Central TB Division, the main governmental department dealing with the control and reduction of tuberculosis cases through the National Tuberculosis Elimination Programme (NTEP), have risen from $76 million USD from 2016 to nearly $2.5 billion USD, reflecting India ’ s promise to eradicate tuberculosis by 2025, but this still continues to fall short of their goal of a 2.5% GDP budget allocation, though this may change in the coming years. Additionally, the possibility of false data reporting, internal corruption, and underrepresentation among numerous regions threatens to derail these seemingly promising statistics. Just the baseline upscaling, without even factoring in DOTS and medical private sector regulation, is already costly and not meeting its GDP allocation goals so far, showing that if India wants to upscale its TB testing and treatment centers without sacrificing quality, a shift in the baseline system is necessary.

Biomedical/Biological/Biochemical

Multidrug-resistant tuberculosis (MDR-TB), harboring much of the same symptoms of regular tuberculosis, including fever, chest pain, general weakness, cough, and sputum production, is a more dangerous form of TB, showing large amounts of resistance to major drug classes and products including rifampicin and isoniazid, both commonly used and powerful first-line drugs to treat TB that are now obsolete to treat MDR-TB. This drug resistance, as mentioned earlier in the introduction, is caused by increasing numbers of efflux pumps in MDR-TB cells that pump out antibiotic drugs intended to kill the pathogen and more enzymes that inactivate drugs like rifampicin and isoniazid. As already discussed, patient and sole care-related factors that may exacerbate antimicrobial resistance include inappropriate use of TB drugs and formulations along with premature treatment interruption, causing drug resistance.

Currently, multiple prescription drugs that can treat multidrug-resistant tuberculosis now are in good supply, although the pathogen can threaten these drugs too if resistance goes unchecked into the future. These include second-line drugs like levofloxacin, moxifloxacin (both of which are fluoroquinolones), and combination regimens that include drugs like moxifloxacin, clofazimine, and ethambutol, among others. These combination regimens are commonly used in Direct Observation Therapy Short-Course (earlier described as DOTS), which has had growing global success but still suffers the risk of patient indiscipline and misinformation. This risk, while negligible in the first few decades since antibiotics were introduced to treat tuberculosis due to their great strength, has now become relatively larger, making those same antibiotics powerless against modern infections. Due to this growing resistance, it is imperative for affected nations to focus on widespread access for testing and treatments; in India specifically, as will be discussed in a later section in more detail, the Central TB Division is now hoping to do this.

The actual process of drug resistance is quite complex. Tuberculosis drug resistance occurs when the bacteria that cause TB, Mycobacterium tuberculosis, develop mutations (or are transferred genetic material from other bacteria with resistance genes) that allow them to survive despite the use of anti-TB drugs. These mutations usually become a problem when treatment is not properly followed, as already discussed. For example, mutations in the katG or inhA genes make the bacteria resistant to isoniazid, while mutations in the rpoB gene cause resistance to rifampin, both of which are the top-line drugs to treat tuberculosis. When the bacteria become resistant to both, the condition is called multidrug-resistant TB (MDR-TB). If resistance extends to second-line drugs like fluoroquinolones or injectables, it is called extensively drug-resistant TB (XDR-TB). If the process goes even further and the TB pathogen somehow becomes resistant to all drugs (meaning it is practically impossible to treat with medication), it is called pan-drug-resistant TB (PDR-TB); while there haven’t been much cases of PDR-TB yet, it still remains a looming fear on the horizon should the global public health system continue to neglect drug resistance.

To combat these threats of multidrug-resistance and extensive drug resistance, global public health systems and the modern medical community are focusing a lot on biomedical treatments like novel drug development, new drug therapies, possible applications of immunotherapy, and more. This emphasis on medical conditions, while important, has also come at the expense of neglecting relevant external issues relating to regional cultures, socioeconomic disparities, and other topics that are listed in this paper. While biomedical treatments have been emphasized (especially in India, where , there has been a relatively lack of concern for these conditions, which may include poor living conditions, unsanitary resources (water, food, air), lack of sanitary protocol in everyday life (for example, lack of handwashing), and even certain cultural practices and beliefs that may inadvertently cause this (as was already discussed in a previous section).

Over time, Indian biomedical treatments themselves have changed in efficacy towards treating TB (Ministry of Health and Family Welfare; Govt. of India, 2022). Mass Bacillus-Calmette-Guerin (BCG) vaccine campaigns started in India in 1951, but soon proved ineffective in the 1990s, especially against TB strains in India that had grown more resistant and more strongly attacked the lungs of the victim. Shortly after these campaigns, there was a notable shift towards home-based chemotherapy, employing many of the same drugs that are used today to treat tuberculosis; however, access to these drugs varied in the initial days, and access only got strengthened following the rapid growth of India ’ s pharmaceutical market, which was discussed earlier. The treatments and testing methods for TB, while advanced, are relatively costly and hard to implement; a regular DOTS regimen

As mentioned earlier in the introduction, MDR-TB has proven to be a huge problem over the past few years for the country ’ s public health. The impacts have gotten worse since its discovery in 2012 in a Mumbai hospital, explained by the fact that India continues to have 26% of global TB cases as of 2023 according to the National Institutes of Health (NIH). It has become a public health crisis , as this 26% involves 8.2 million people diagnosed with tuberculosis, 1.23 million of those people dying that year (Mandal, Rao, Joshi, 2023).

While this discussion on the biological and social issues and influential factors related to the current case of MDR-TB has been far-reaching, these factors tend to be caused by underlying flaws in global health systems.

Systemic Flaws

A large part of these discrepancies in healthcare, treatment, and true betterment of the afflicted when it comes to MDR-TB in India is due to the underlying public health system of India. There are multiple flaws with the Indian healthcare system when it started to handle the tuberculosis (and later the rising resistance of later strains), and a lot of it has to do with the main government department tasked with controlling the spread of TB: the Central TB Division, carrying out the the National Tuberculosis Elimination Programme (formerly called the Revised National Tuberculosis Control Programme).

The emphasis in this program largely paints MDR-TB as a public problem, which it essentially is. Usually, the government should ideally ensure public action, not necessarily the individuals, but this may need to change in the future, as the public needs help from experts, advocates, pressure groups, and lobbyists to represent their perspectives and interests (which maybe are not being considered by the Central TB Division currently). This conveys that multiple individual actors in Indian society, while having the potential to influence health policies sociopolitically, are usually experiencing a power imbalance, with higher-status actors having more power to influence unlike lower-status actors like the enormous Indian middle class. Systematically speaking, inclusion of all local groups of actors, including public health practitioners, health planners, policy makers, and patients themselves, might seem impractical from a financial and economic standpoint but it is absolutely necessary for this form of equity to show when constructing a public health system.

Additionally, funding tends to gravitate towards the political and medical interests (which tend to be more high-paying and lucrative), which affect the health decisions the Central TB Division takes. This is especially true in defining TB, exerting medical social control over the concept of the disease. This fascinating social dynamic leads to an interesting clash: should we keep the Central TB Division (basically the government) or the vocal actors (that bring in important perspectives, like private practitioners, non-governmental organizations, and researchers) out of the limelight.

Weak data exists for the TB epidemic, as there was a lack of data from the unregulated and diversified private sector (more on this later). When a large TB epidemic sprouted up in 2013, the government took data on a few hospitals in Gujarat and Chennai over the course of a few weeks, hoping to extrapolate and adjust these numbers to represent the whole nation. The data showed 1-3% MDR-TB in Gujarat and Chennai, with 13-17% resistance in previously treated cases. In addition, 3% of TB patients in the Gujarat and Chennai studies are considered to have native MDR-TB (in other words, they had it already when they came into the hospital), while 17% of TB patients were considered to have acquired MDR-TB (meaning they most probably acquired the strain during their hospital stay). This continues to show how drug resistance is especially opportunistic in nosocomial, or hospital-acquired, infections.

Of course, even when assuming that the Central TB Division honestly collected the data as best they could, there are still general epistemological questions to be asked when considering the validity of the data as a whole. For example, mortality statistics may be inadequate; according to sociologist Dr. John B. McKinlay, many conditions may be responsible for deaths (and not just the one that the patient came to the hospital with). In addition, changes in disease classifications and social norms and expectations of health illnesses can also negatively influence these statistics (for example, death by epilepsy might have been perceived as negative spiritual outbursts in an earlier time). However, we should still be able to measure those limitations and hopefully account for them, especially considering these limitations may apply equally to all studies involving mortality stats, especially ones involving TB hospital deaths.

However, critics have a different outlook. Looking at the fishy nature of these numbers and statistics, they feel that the government is not facing up to the problem’ s scope, exaggerating overly optimistic TB data that may give a false sense of security when a 3% nationally-extrapolated rate of MDR-TB, doubting whether the Gujarat and Chennai studies were even representative of the total MDR-TB numbers. In fact, an unnamed microbiologist in these studies mentioned that the government doesn’t like to see high numbers in MDR-TB rates, and therefore the political pressure is on to keep the numbers low (whether it was actually achieved or not). Due to this, most critics are in favor of more rationality and quality of innovations to properly map MDR-TB and bring transparency with the public.

While some of this has already been mentioned in the sociocultural factors section of this paper, multiple drawbacks in the system lead to a lot of discrepancies in the health infrastructure of health facilities like hospitals and clinics. A lot of cases (according to the paper linked at the top of the section) occur due to mismanagement and poor treatment; many times, it ends up being in the hands of the patients, but also can stem from the health professionals in establishments. Central TB Division officers label MDR-TB as a problem created by external factors and the actors themselves (due to lack of regulation and mistreatment at the most direct level, not to mention nonadherent patients). However, critics argue that this is just a narrative pushed by the program to hide its own shortcomings. In reality, this ends up being a little bit of both; while drug pressure does exist with growing strength of TB with each infection and higher malnutrition of a country (making a better “playing ground”).

To add on, DOTS and other standard current TB treatments can also fail if improper direct supervision and little cooperation with the private sector occurs. The private sector, consisting of about 63 million microbusinesses (with over 10,000 of those microbusinesses as recognized health organizations), is probably the most large and far-reaching influential organizational entity in India, across both urban and rural areas (although they do tend to be way more concentrated in urban areas). One issue with the current health system is a noticeable lack of communication and coordination with the private sector, which can lead to many sometimes unscrupulous local healthcare workers deliver improper treatments and drugs to TB patients and may not report proper numbers, distorting the true validity of current data and the effectiveness of the program. If the private sector ends up being regulated by the Central TB Division, multiple local healers and ethnomedical professionals can be held accountable while also having their voices heard on possible holistic treatments, leading to breakthroughs in TB treatment and curbing the rise of resistance.

Conclusion, and Suggestions For the Way Forward

Addressing the growing MDR-TB crisis, in summary, will need a lot more avenues of research and problem-solving than the current steps and solutions being devised to merely keep it at bay. The high emphasis on the biomedical aspects of tuberculosis in India (in general) is unfortunately masking the equally important sociocultural aspects and phenomena that occur with Indian tuberculosis. Therefore, to address these aspects as well, an integrated medical approach is needed; the medical community should not only address the biomedical aspects of tuberculosis, but also take into account the sociocultural and economic aspects which are arguably equally important in vulnerable areas like India.

However, this is easier said than done when trying to scale the full scope of this ambition. However, apart from making necessary changes to the Indian public health system, a great starting point is to build cultural competency and sensitivity with Indian patients, no matter the health professionals ’ qualifications, degree, or amount of knowledge. Respecting the patients ’ perspectives, and smoothly guiding them in the right direction with their cultural beliefs about TB and the appropriate hybrid treatment plans that can combine Ayurvedic medicine and allopathic medicine with alleviations to social conditions, can ultimately result in a more culturally respectful environment in multiple rural and religiously devoted regions that can holistically address TB’ s rising antimicrobial resistance. It can also help break stereotypes commonly associated with the healthcare field, various types of health professionals and treatments, and personal psychological evaluations about one ’ s own health.

In a time when systemic and socioeconomic discrepancies have exacerbated the destructive nature of the recent COVID-19 pandemic in multiple countries, these disparities can serve as a learning moment for India and its Central TB Division to improve their main public health system, mode of testing, cost-effectiveness, reach, and sociocultural sensitivity. Tuberculosis is a curable disease, and yet it is still the most prevalent infectious disease in India to this day; hopefully that changes soon.

Bibliography

Aftab, A. (2024, June 27). Small business, big impact: Empowering women for Success. IFC. https://www.ifc.org/en/stories/2024/small-business-big-impact

Asian Pacific American Advisory Group. (2011). Health Care Providers ’ handbook on Hindu patients. AAHII Info. https://aahiinfo.org/wp-content/uploads/2023/04/Healthcare-Handbook_Hindu.pdf Centers of Disease Control and Prevention. (2024). History of W orld TB Day.

Centers for Disease Control and Prevention. https://www.cdc.gov/world-tb-day/history/?CDC_AAref_Val=https%3A%2F%2Fwww.cdc.gov %2Ftb%2Fworldtbday%2Fhistory.htm

Deshmukh, R. D., Dhande, D. J., Sachdeva, K. S., Sreenivas, A., Kumar, A. M. V., Satyanarayana, S., Parmar, M., Moonan, P. K., & Lo, T. Q. (2015, August 14). Patient and provider reported reasons for lost to follow up in MDRTB treatment: A qualitative study from a drug resistant TB Centre in India. PLOS ONE. https://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0135802

Government of India. (2025, September 26). About US – central tuberculosis division. Central Tuberculosis Division. https://tbcindia.mohfw.gov.in/about-us/

India, F. (2025, March 5). Poverty rate in India [2024]: Trend over the years and causes. Poverty rate in India: Trend over the years and causes. https://www.forbesindia.com/article/explainers/poverty-rate-in-india/90117/1

Lantz, P. M., Goldberg, D. S., & Gollust, S. E. (2023, April 25). The perils of medicalization for population health and health equity – lantz – 2023 – the Milbank Quarterly – Wiley Online Library. Wiley Online Library. https://onlinelibrary.wiley.com/doi/10.1111/1468-0009.12619

Make In India. (2025). Sector highlights: Pharmaceuticals | Make in India. https://www.makeinindia.com/sector-highlights-pharmaceuticals

Mandal, S., Rao, R., & Joshi, R. (2023a, March 24). Estimating the burden of tuberculosis in India: A modelling study. Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine. https://pmc.ncbi.nlm.nih.gov/articles/PMC10353668/#:~:text=We%20estimated%20total%20 TB%20incidence,was%2023%20and%2027%20respectively

Mandal, S., Rao, R., & Joshi, R. (2023b, March 24). Estimating the burden of tuberculosis in India: A modelling study. Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine. https://pmc.ncbi.nlm.nih.gov/articles/PMC10353668/#:~:text=We%20estimated%20total%20 TB%20incidence,was%2023%20and%2027%20respectively

Mandaviya, M. (2022, March 24). India TB Report 2022 – coming together to end TB … TBC India. https://tbcindia.mohfw.gov.in/wp-content/uploads/2023/05/TBAnnaulReport2022.pdf

Watters, E. (2010, January 10). The Americanization of mental illness – The New York Times. The New York Times. https://www.nytimes.com/2010/01/10/magazine/10psyche-t.html

World Health Organization. (2024). Tuberculosis resurges as top infectious disease killer. https://www.who.int/news/item/29-10-2024-tuberculosis-resurges-as-top-infectious-disease-kill er

About the author

Akshar Belaguly

Akshar is currently a freshman at Brown University concentrating in Biochemistry and Molecular Biology and wrote the paper while he was a senior at Gretchen Whitney High School in Cerritos, California. Some of his academic interests include biochemistry, genetics, and analytical chemistry, but he also has a deep fascination with medical anthropology that will hopefully give him holistic perspectives in his journey to medical school.

In addition, Akshar has also been part of his school’s Science Olympiad team, loves to watch and play cricket and basketball, and loves to spend time with his family in his free time.

The post The Cultural Influences of Medicalization: How Culture Influences Tuberculosis In India appeared first on Exploratio Journal.

Abstract

Obesity is often misunderstood as a simple matter of overeating or moving too little. In reality, it’s a deeply rooted physiological condition caused by the breakdown of several key systems in the body. This paper examines the development of obesity through five closely interconnected biological mechanisms: fat storage (adiposity), insulin resistance, energy balance, hunger signaling via leptin, and chronic low-grade inflammation. These systems work together to regulate how we store energy, control appetite, burn calories, and respond to stress. When one system begins to fail, like when fat cells grow too large or the brain stops responding to fullness signals, the others often follow, creating a cycle that makes weight gain easier and weight loss harder. The paper also highlights how prevention needs to go far beyond willpower or dieting. Real solutions come from supporting the body’s natural systems through better sleep, balanced eating, physical activity, stress management, and more. Understanding the biology behind obesity helps us replace blame with empathy and find smarter, more lasting ways to support health.

Key terms

Introduction

Obesity is not just a personal struggle; it is a public health crisis that affects over 650 million adults and 124 million children worldwide. Traditional narratives have oversimplified its causes, framing obesity as a result of poor choices, lack of exercise, or overeating. However, such views ignore decades of research that reveal a much deeper truth: obesity is a chronic physiological disorder involving multiple, interdependent systems that govern metabolism, hormonal signaling, energy storage, and immune response.

Rather than a purely behavioral issue, obesity reflects a breakdown in metabolic homeostasis, the body’s ability to maintain internal balance in response to changing environments. At its core, obesity is the result of a persistent imbalance between energy intake and expenditure, complicated by the dysregulation of hormones such as insulin and leptin, altered fat cell function, and chronic low-grade inflammation.

This paper explores the physiological mechanisms that cause obesity and the interventions that can help prevent or reverse it. We focus on five interconnected biological systems:

• Adiposity (fat accumulation and behavior of fat tissue)
• Insulin resistance (metabolic inefficiency and hormonal disruption)
• Energy balance (caloric intake vs. expenditure dynamics)
• Leptin resistance (dysfunctional satiety signaling)
• Inflammation (chronic immune activation affecting metabolism)

By understanding how these systems interact, we can move toward more effective, biologically grounded strategies to prevent obesity not only at the individual level, but across public health, clinical, and policy landscapes.

1. Adiposity: The Biology of Fat Storage

Adiposity is the quantity and distribution of fat, and that fat, as active tissue, is capable of storing excess energy in the form of triglycerides and communicating with the brain and immune system through hormones and messengers such as leptin, adiponectin, and resistin, assists in thermoregulation, and contributes to the body’s response to infections. (Neufingerl and Eilander 2021)

It comes in two primary forms: white adipose tissue (WAT), the primary storage type that also secretes hormones to regulate appetite and guide energy balance, and brown adipose tissue (BAT), rich in mitochondria that burns calories to produce heat through thermogenesis. It is more abundant in infants, and in adults is found in small quantities, which can be activated with safe cold exposure or during some physical activity. Immune cells, such as macrophages, release the inflammatory factors TNF-α and IL-6 while protective adiponectin falls below a certain threshold. This is known as the ‘adipose tissue dysfunction’. This phenomenon lowers the insulin signal and increases the risk for metabolic disease. From a pathobiology perspective, the location of fat tissue is important because subcutaneous fat located just under the skin is usually neutral, sometimes even protective, and visceral fat that envelops the liver, pancreas, and intestines is pathologically active and produces and excretes inflammatory factors and free fatty acids bound for the liver via the portal vein. This visceral fat is associated with type 2 diabetes, heart disease, hypertension, and non-alcoholic fatty liver disease. These behavioral patterns begin at a young age. For example, by performing daily exercise, teens can decrease their fat stores, which improves the functions of the fat cells. These exercise habits, coupled with the intake of healthy unsaturated fatty acids found 5 in nuts, olive oil, and fatty fish, the avoidance of ultra-processed foods, proper hydration that facilitates the lipolytic response, and the application of safe cooling in daily life to invigorate brown fat, shift the ratio of subcutaneous to visceral fat in the desired direction while maintaining the long-term functionality of the adipose tissue. (Guarino et al. 2023)

2. Insulin Resistance: When Cells Stop Listening

Insulin, which is produced in the pancreas, is a hormone that functions as a ‘key’ that enables the cells in the body to absorb blood sugar. Blood sugar (or glucose) comes from the food we eat, and in particular carbohydrates, which serve as energy for anything from the movement of the muscles to activities done in the brain. When blood glucose is well managed in the body, these cells extract the glucose from the blood and either use it for immediate energy or store it for later use. Save this process, other functioning organs in the body would not get energy, and along with that, blood sugar levels would go uncontrolled.

Insulin is like a key that lets sugar from your food into your cells so they can make energy. With insulin resistance, the locks on the cells get sticky. The key still fits, but the door is hard to open. More sugar stays in your blood, so your pancreas sends out extra insulin to try to force it in. Constantly high insulin, called hyperinsulinemia, makes your body store more fat, especially in your belly, and increases the chance of developing type 2 diabetes over time.

When your body stops responding well to insulin, the effects show up everywhere, because your muscles do not pull in sugar for energy and you feel tired or weak after carb-heavy meals, your liver keeps making sugar even when you do not need it and your blood sugar rises, your fat cells get told by high insulin to store more and belly fat often increases, and your brain’s dopamine system can be thrown off so cravings for sweet or fatty foods get stronger and overeating becomes easier. Early signs include feeling wiped out after eating, 6 getting powerful and frequent cravings for sugary or starchy foods, noticing belly fat that does not budge with normal efforts, and sometimes seeing dark, velvety skin patches on the neck or underarms called acanthosis nigricans.

What drives this problem are habits like eating lots of added sugar and refined grains that spike blood sugar and insulin, long periods of sitting that make muscles worse at using sugar, and ongoing stress that raises cortisol and pushes blood sugar up. What helps most are steady changes such as moving every day with walking, biking, swimming, or strength training so muscles listen to insulin better, cutting back on added sugars and refined carbs while eating more fiber from whole grains, vegetables, beans, and lentils to smooth blood sugar, using a consistent daytime eating window of about ten hours if it suits you so insulin can drop between meals, practicing mindfulness, deep breathing, or yoga to lower stress, and protecting sleep so hormones stay in rhythm. The big idea is simple: insulin resistance is usually a response to a long-term mismatch in food, movement, stress, and sleep, so spotting it early in your teens or early twenties and making steady changes can lower your risk of type 2 diabetes later.

Improved lifestyle habits determine levels of insulin resistance. Diets high in added sugars and refined grains cause blood glucose and insulin levels to spike intermittently, leaving your body with no option other than to “tune out” insulin over time. Prolonged periods of physical inactivity result in the muscular system losing the ability to absorb glucose as blood levels of the sugar increase. Chronic stress also adds insult to injury because of the stress hormone, which elevates blood sugar levels and promotes insulin resistance. The positive news here is that gradual changes work. Exercise most days of the week, including low-impact activities: walking, biking, swimming, and weight lifting, to strengthen the ability of muscle tissues to respond to insulin. Avoid added refined sugars and carbs and consume more whole, plant sources of fiber, including whole grains, vegetables, and legumes, to stabilize blood sugar levels. Time-restricted feeding, or an eating schedule with a shorter time of eating around ten 7 hours, works well for some because it promotes a more sustained drop in insulin between meals. Stress is more effectively managed using mindfulness, breathing exercises, and yoga, and sleep quality must be prioritized in order to regulate hormone levels.

By understanding insulin resistance not as a random malfunction but as the body’s response to a sustained imbalance in diet, activity, and stress, we can take proactive steps to restore metabolic health. Early intervention during adolescence or young adulthood can prevent years of progression toward type 2 diabetes and related conditions, making it a vital focus in obesity prevention efforts. (McGlynn et al. 2022)

Figure 1: Insulin resistance is a type of reaction in a person’s body, especially muscle cells, that makes it less responsive to insulin. By having less reactive insulin within the body, normally it would facilitate the amount of glucose consumed to either store it as an energy source, but since it is getting resisted, the cells do not respond correctly to the insulin signal. This leads to a reduced glucose intake and an increased spike in glucose levels.

3. Energy Balance: The Calorie Equation and Beyond

Energy balance is the match between the energy you take in from food and drinks and the energy your body uses for living, moving, and digesting. While it looks like simple math (eat more than you burn to gain, burn more than you eat to lose), your body constantly adapts, so the balance shifts. (Pardo et al. 2021)

Most daily burn comes from basal metabolic rate (BMR), roughly 60–70%, which powers your heart, lungs, brain, and cells even at rest. Physical activity adds a variable share that includes workouts, sports, walking, chores, and small movements like standing and fidgeting (NEAT). Digestion also costs energy via the thermic effect of food (TEF), with protein costing more than carbs or fat. Brown fat can add a small cold-activated boost by turning stored energy into heat. Harsh calorie cuts trigger metabolic adaptation (adaptive thermogenesis) that lowers BMR and, with hormone shifts that raise hunger and reduce fullness, slows loss and promotes regain. Energy imbalance comes in three forms: positive (intake > burn, weight rises), negative (intake < burn, weight falls, but too-large deficits can cause muscle loss, nutrient gaps, and slower metabolism), and neutral (intake ≈ burn, weight holds), and small changes can tip you between them. Long-term balance works best when you support the system rather than obsess over every calorie by building and keeping muscle with resistance training to raise BMR, eating enough protein to protect muscle, increase fullness, and boost TEF, avoiding crash diets that cause large slowdowns, and keeping consistent routines for meals, sleep, and movement. For teens and young adults, habits formed now tend to stick, so favor nutrient-dense foods, daily activity you enjoy, and sustainable patterns, and treat energy balance as a lifelong rhythm rather than a short-term fix to give yourself the best chance at a healthy weight and steady energy. (Kalaitzopoulou et al. 2023)

Figure 2: Energy balance is the amount of calories consumed through food and drink that is equivalent to the amount of calories the body has burned down to equal it out. There are three types of energy balance. A positive energy balance is a state where a person consumes an excessive amount of calories that the body cannot expend. This results in increased adiposity (Obesity) and weight gain. A negative energy balance is the result of taking way too less calories compared to what the body is burning. This will result in weight loss. Lastly, neutral energy balance is the type where the body is equally regulating the amount of calories intake, while the calories are equally burned down. This will lead to weight maintenance.

4. Leptin: The Hunger-Regulating Hormone

Think of leptin as your body’s built-in fuel gauge. It’s a hormone made mostly by your fat cells, and its job is to keep your brain updated on how much energy you have stored. When your body has plenty of fuel, leptin travels through your blood to the hypothalamus, the brain’s control center for hunger, energy, and weight, and delivers a simple message: “We’re good. You can slow down on eating and speed up on burning energy.”

When this system is working as it should, you naturally feel satisfied after eating, your metabolism hums along, and you have the energy and motivation to be active. After a meal, leptin levels rise, telling the brain that your energy needs are met. The brain responds by easing hunger signals and nudging your body to burn a little more. Maybe through movement, maybe through heat production, in a neat feedback loop that helps keep your weight steady without you having to think about it.

When the leptin system breaks, it is called leptin resistance. Leptin levels are high, sometimes very high, but the brain does not “hear” the message. The hunger off-switch feels stuck. Even with plenty of stored energy, the brain acts like fuel is low, so hunger goes up and calorie burn slows down. You can feel hungry soon after eating, and your body holds on to fat. More body fat makes more leptin, which makes the resistance worse, so the cycle repeats. Several forces can throw this system off. Inflammation in the brain, especially in the hypothalamus, can block leptin’s signal. Diets heavy in sugary, ultra-processed, or greasy foods raise oxidative stress, which damages the brain’s appetite pathways. Poor sleep makes it harder too; even one short night can lower leptin, raise ghrelin, and push stronger cravings the next day. Frequent overeating can also numb leptin receptors, the way loud noise can numb hearing.

Leptin affects more than hunger. It interacts with dopamine and serotonin, which shape mood, motivation, and pleasure, so weak leptin signaling can make you feel less driven to move and more likely to eat for comfort. It also affects fertility. If the brain thinks energy is low, it may slow or pause reproductive functions, even when the body has enough fuel. Leptin also links to the thyroid, which sets metabolic speed, so leptin problems often come with a slower metabolism.

The upside is that leptin sensitivity can improve. Getting a solid 8–9 hours of sleep each night helps keep hormone rhythms steady. Regular movement, especially strength training and cardio, reduces brain inflammation and helps leptin signals get through. Omega-3 fats from foods like salmon, walnuts, and flaxseed can also help calm brain inflammation. And avoiding constant snacking, particularly on processed foods, lets leptin rise and fall naturally so your brain has a chance to “hear” it again. (Besci et al. 2023)

Figure 3: Leptin is a peptide hormone made mainly by fat cells, and its blood level reflects total fat stores. Its primary role is to signal the hypothalamus that energy is sufficient, which reduces appetite, adjusts energy expenditure and sympathetic tone, and helps coordinate reproductive, thyroid, and immune functions. In common obesity, leptin levels are high but signaling is blunted (“leptin resistance”), so added leptin seldom causes weight loss, whereas replacement helps in true deficiency and some lipodystrophies. (Kamal-Rahmouni et al. 2002)

5. Inflammation: The Immune System’s Double-Edged Sword

Inflammation is the body’s built-in alarm system. It’s there to protect us when something goes wrong, like when you cut your finger, catch a cold, or sprain your ankle. In those moments, your immune system sends in its “first responders.” The area becomes red, warm, and swollen because immune cells are flooding in to fight off germs, clear away damage, and start the healing process. Once the job is done, the alarm switches off and your body goes back to normal. That’s acute inflammation, and it’s a good thing.

However, sometimes the body’s alarm does not shut off; it stays low and constant for weeks or years, which is called chronic low-grade inflammation, and it quietly damages tissues over time. In obesity, it often starts in fat tissue, where overgrown fat cells get stressed and send out distress signals that call in immune cells called macrophages; these cells release inflammatory chemicals such as TNF-alpha and IL-6 that make cells ignore insulin and handle sugar poorly, and blood tests often show higher C-reactive protein (CRP), a sign that inflammation is active across the body. This slow fire spreads: in the gut it can weaken the lining and let harmful bacteria slip into the bloodstream (leaky gut), in the brain it can disturb the hypothalamus so hunger and fullness signals break down and leptin resistance develops, in the liver it pushes fat buildup that can lead to non-alcoholic fatty liver disease (NAFLD), and in blood vessels it speeds plaque growth, which raises the risk of heart attack and stroke.

What you eat, how much you move, and how you handle stress can all influence inflammation. Diets full of sugary drinks, processed meats, fried foods, and packaged snacks make it worse by increasing oxidative stress, a kind of cellular “rusting” that triggers inflammation. Not moving enough is another problem, because muscles release special anti-inflammatory chemicals when you exercise. High stress levels keep the hormone cortisol elevated, which in turn can push inflammation higher. And when you don’t sleep well, your immune system loses its rhythm, tipping the balance toward more inflammation. (Nagorcka-Smith et al. 2022)

The good news is that you can turn the alarm back down. Eating more anti-inflammatory foods, like berries, leafy greens, olive oil, and fatty fish, gives your body nutrients that help calm the immune system. Fermented foods like yogurt, kefir, or kimchi can feed healthy gut bacteria, which in turn protect against inflammation. Moving your body regularly, even just a brisk 20-minute walk, helps your muscles release anti-inflammatory signals. Learning to manage stress through things like meditation, deep breathing, or simply taking time to relax can lower cortisol levels. And making sleep a priority, aiming for 8 to 9 hours most nights, gives your immune system the time it needs to reset. (Nikooyeh and Neyestani et al. 2021)

Figure 4: In nutrition, inflammation is the body’s immune signaling state as affected by diet and body fat. Acute inflammation helps repair, but chronic low-grade inflammation arises with energy excess and poor food quality, raising markers like hs-CRP, IL-6, and TNF-α and promoting insulin resistance, cardiovascular disease, and fatty liver, while ultra-processed foods, refined carbs, trans fats, and heavy alcohol push inflammation up and whole-food patterns rich in vegetables, fruits, legumes, whole grains, nuts, olive oil, omega-3 fish, and fiber that feeds the gut microbiome tend to bring it down, with weight control, regular activity, sleep, and stress management strengthening the effect.

The Cycle: How All Five Systems Work Together

Obesity isn’t caused by one thing; it’s caused by many things going wrong at once:

These problems feed into each other, making it harder to break the cycle. But the good news is: small changes can help reset the system.

Prevention

You don’t need to be perfect. But supporting your body’s natural systems goes a long way in keeping obesity away.

To support metabolic flexibility, try intermittent fasting to improve insulin and leptin and vary your calorie intake across days through caloric cycling, and if you are under 18 or have a medical condition consult a clinician before fasting; eat anti-inflammatory foods by prioritizing whole, unprocessed meals, colorful fruits and vegetables, and healthy fats such as nuts, seeds, olive oil, and fatty fish instead of fried foods; manage stress with short daily meditation, breathing exercises, or yoga and by journaling or talking with a friend, since chronic stress raises cortisol and can promote belly fat; and align with your body’s clock by eating during daylight hours, sleeping at night, and keeping a consistent bedtime because your hormones follow a daily rhythm that works best on a regular schedule.

Conclusion

Obesity is not a simple choice. It’s not a result of laziness or weakness. It’s a physiological condition caused by complex changes in the body’s systems, especially the way fat is stored, sugar is used, hormones are regulated, and the immune system responds to stress. But that also means obesity can be prevented. Not just with willpower, but with knowledge, consistency, and self-care. When we understand how the body works, we can give it what it needs to function better. Instead of focusing only on weight, we should focus on balance between eating and moving, between sleeping and waking, between stress and rest. That’s the key to helping your body feel strong, energized, and healthy.

References

Besci, Özge, Sevde Nur Fırat, Samim Özen, Semra Çetinkaya, Leyla Akın, Yılmaz Kör, Zafer Pekkolay, Şervan Özalkak, Elif Özsu, Şenay Savaş Erdeve, Şükran Poyrazoğlu, Merih Berberoğlu, Murat Aydın, Tülay Omma, Barış Akıncı, Korcan Demir, and Elif Arioglu Oral. 2023. “A National Multicenter Study of Leptin and Leptin Receptor Deficiency and Systematic Review. ” The Journal of Clinical Endocrinology & Metabolism 108(9):2371–88. doi:10.1210/clinem/dgad099.

Guarino, Miriana, Lorena Matonti, Francesco Chiarelli, and Annalisa Blasetti. 2023. “Primary Prevention Programs for Childhood Obesity: Are They Cost-Effective?” Italian Journal of Pediatrics 49(1):28. doi:10.1186/s13052-023-01424-9. 17

Kalaitzopoulou, Ioustini, Xenophon Theodoridis, Evangelia Kotzakioulafi, Kleo Evripidou, and Michail Chourdakis. 2023. “The Effectiveness of a Low Glycemic Index/Load Diet on Cardiometabolic, Glucometabolic, and Anthropometric Indices in Children with Overweight or Obesity: A Systematic Review and Meta-Analysis. ” Children 10(9):1481. doi:10.3390/children10091481.

McGlynn, Néma D., Tauseef Ahmad Khan, Lily Wang, Roselyn Zhang, Laura Chiavaroli, Fei Au-Yeung, Jennifer J. Lee, Jarvis C. Noronha, Elena M. Comelli, Sonia Blanco Mejia, Amna Ahmed, Vasanti S. Malik, James O. Hill, Lawrence A. Leiter, Arnav Agarwal, Per B. Jeppesen, Dario Rahelić, Hana Kahleová, Jordi Salas-Salvadó, Cyril W. C. Kendall, and John L. Sievenpiper. 2022. “Association of Low- and No-Calorie Sweetened Beverages as a Replacement for Sugar-Sweetened Beverages With Body Weight and Cardiometabolic Risk: A Systematic Review and Meta-Analysis. ” JAMA Network Open 5(3):e222092. doi:10.1001/jamanetworkopen.2022.2092.

Nagorcka-Smith, Phoebe, Kristy A. Bolton, Jennifer Dam, Melanie Nichols, Laura Alston, Michael Johnstone, and Steven Allender. 2022. “The Impact of Coalition Characteristics on Outcomes in Community-Based Initiatives Targeting the Social Determinants of Health: A Systematic Review. ” BMC Public Health 22(1):1358. doi:10.1186/s12889-022-13678-9.

Neufingerl, Nicole, and Ans Eilander. 2021. “Nutrient Intake and Status in Adults Consuming Plant-Based Diets Compared to Meat-Eaters: A Systematic Review. ” Nutrients 14(1):29. doi:10.3390/nu14010029.

Nikooyeh, Bahareh, and Tirang R. Neyestani. 2021. “Effectiveness of Various Methods of Home Fortification in Under-5 Children: Where They Work, Where They Do Not. A Systematic Review and Meta-Analysis. ” Nutrition Reviews 79(4):445–61. doi:10.1093/nutrit/nuaa087.

Pardo, Marta R., Elena Garicano Vilar, Ismael San Mauro Martín, and María Alicia Camina Martín. 2021. “Bioavailability of Magnesium Food Supplements: A Systematic Review. ” Nutrition (Burbank, Los Angeles County, Calif.) 89:111294. doi:10.1016/j.nut.2021.111294.

The author utilized an artificial intelligence tool, Google Gemini, and Perplexity to enhance the clarity and readability of the writing. All final content, critical interpretation, and responsibility for accuracy remain solely with the author.

About the author

Ryan Jung

Ryan is currently a junior attending school in Suffield, Connecticut.

The post Hack Your Hunger: How to Reset Your Body’s Fuel Gauge appeared first on Exploratio Journal.