A Psychometric Investigation of Racial Trauma Symptoms Using a Semi-Structured Clinical Interview With a Trauma Checklist (UnRESTS)
Why this work is in the frame
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Bibliographic record
Abstract
The term racial trauma is used to describe the cumulative distressing and traumatizing effects of racism in all of its forms, and it closely resembles the construct of posttraumatic stress disorder (PTSD). This investigation aims to increase our understanding of racial trauma by comparing the characteristics of those with a clinically-relevant diagnosis of racial trauma to those without, based on the findings of a clinical semi-structured interview and symptom checklist for assessing racial trauma, the University of Connecticut Racial Ethnic Stress and Trauma Survey (UnRESTS), administered to a diverse group of adults (N = 97). This paper extends prior work on racial trauma by examining the correlations between racial trauma and validated self-report measures of discriminatory distress, controlling for racialization. We examine the correlation between a clinically-relevant diagnosis of racial trauma and racial/ethnic identity. We also compare racism-related PTSD symptoms in those with and without racial trauma to inform clinical assessment. Finally, we examine the factor structure of racial trauma symptoms using the 24 items from the UnRESTS PTSD symptom checklist and compare these to current DSM-5 models. The structure of racial trauma symptoms differed from the DSM-5 4-factor model, as do other PTSD models in the research literature. Clinical and research implications are discussed.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it