Cumulative Disadvantage and Black-White Disparities in Life-Course Health Trajectories
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
In this study, the authors use longitudinal data from the Panel Study of Income Dynamics and growth curve models to examine the utility of the concept of cumulative disadvantage as an explanation for race differences in life-course health (self-rated) in the United States. The authors ask whether socioeconomic resources equally benefit the health of Blacks and Whites, or if Whites receive higher rates of return to resources across the life course. The authors find that the relationship differs depending on the indicator of socioeconomic status that is examined. Education does not offer the same advantages for the health of Blacks as it does for Whites, particularly at higher levels of education, and this is compounded with age. In contrast, returns to income and wealth are similar for Blacks and Whites, and these resources remain equally important to protecting the health of Blacks and Whites across the life course. Over time, Blacks are at an increasing health disadvantage relative to Whites, a result that is not attenuated by educational attainment.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 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 it