Perceived Racial Discrimination as an Independent Predictor of Sleep Disturbance and Daytime Fatigue
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Perceived discrimination is a potential cause of racial and ethnic disparities in health. Disturbed sleep may serve as a mechanism linking perceived racism with health consequences. This study investigates data from 7,148 adults from Michigan and Wisconsin who participated in the 2006 Behavioral Risk Factor Surveillance System. Hierarchical logistic regression analyses explored associations between perceived racial discrimination and self-reported sleep disturbance and daytime fatigue. Sleep disturbance and daytime fatigue were reported in 19% and 21% of the sample, respectively. Black/African American respondents (21%) report perceiving worse experiences, compared to people of other races, when seeking health care at higher rates than non-Hispanic White respondents (3%). Results from logistic regression models show that perceived racial discrimination is associated with increased risks of sleep disturbance (odds ratio [OR] = 2.62, p < .0001) and daytime fatigue (OR = 2.07, p < .0001). After adjustment for all covariates, perceived discrimination remains a significant predictor of sleep disturbance (OR = 1.60, p = .04). The interaction between perceived racism and race (Black/African American vs. non-Hispanic White) was nonsignificant. This population-based research adds to the growing body of data, suggesting that perceived racism may impact health via its influence on sleep-wake behaviors.
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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 | 0.000 | 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) | 0.002 | 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