Race-based biases in psychological distress and treatment judgments
Bibliographic record
Abstract
Racism creates and sustains mental health disparities between Black and White Americans and the COVID-19 pandemic and ongoing harassment directed at Black Americans has exacerbated these inequities. Yet, as the mental health needs of Black Americans rise, there is reason to believe the public paradoxically believes that psychopathology hurts Black individuals less than White individuals and these biased distress judgments affect beliefs about treatment needs. Four studies (two pre-registered) with participants from the American public and the field of mental health support this hypothesis. When presented with identical mental illnesses (e.g., depression, anxiety, schizophrenia), both laypeople and clinicians believed that psychopathology would be less distressing to Black relative to White individuals. These distress biases mediate downstream treatment judgments. Across numerous contexts, racially-biased judgments of psychological distress may negatively affect mental healthcare and social support for Black Americans.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| 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".