Colorism and Health Inequities among Black Americans: A Biopsychosocial Perspective
Bibliographic record
Abstract
The mechanisms generating skin-tone-based health inequities among ethnic Black Americans remain poorly understood. To address this gap, our study advances a novel biopsychosocial model of embodied colorism-related distress. We test this model with survey and biomarker data from a community sample of working-age Black adults from Nashville, Tennessee (2011-2014; N = 627). Relying on self-rated, interviewer-rated, and discordant skin tone measures, our analyses reveal that Black adults who perceive themselves as dark-skinned tend to have a lower sense of mattering and shorter telomeres, a biomarker of accelerated cellular degradation and aging, relative to their peers who perceive their skin to be lighter. These patterns hold across various social contexts and regardless of interviewer-rated skin tone, indicating that subjective skin tone may be a particularly robust gauge of colorism-related stress processes. Our study reveals critical and previously unexplored biopsychosocial mechanisms linking colorism to health inequity.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".