Understanding the Emotional Toll of Racial Violence on Black Individuals’ Health
Bibliographic record
Abstract
This paper discusses the pivotal role emotions can play in the higher prevalence of disease and mortality in Black populations in North America. There is a large body of research on the potentially harmful effect of negative emotions upon physical well-being. However, many scholars continue to interpret this link via a biological and reactive lens of emotion. By largely disentangling the embodiment of emotions from the traditional biological framework to which they are typically tied, we seek to analyze the nexus of race, emotion, and health through political, historical, and even ontological lenses. This analysis leverages Barrett’s theory of constructed emotion to elucidate the tangible impact of emotion on physical well-being and, in conjunction with Afropessimist metatheory on race, the potential contribution to understanding premature mortality among Black populations in North America. Barrett’s theory offers insight into how the persistent experience of negative emotions related to race can disrupt the delicate balance of an individual’s body-budget. The detrimental impact of White supremacy’s affective classifications and associated emotion concepts on Black populations is a stark reality, contributing significantly to daily health challenges faced by these communities in North America.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".