Racial Limitations on the Gender, Risk, Religion, and Politics Model
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Risk aversion dampens political participation and heightens religiosity, with concentrated effects among women. Yet, little is known about how intersecting identities moderate these psychological correlates of religiosity and political engagement. In this paper, we theorize that the risk-religion-politics relationship is gendered and racialized. Using a nationally representative survey, we show that political participation is more strongly correlated with risk for Black women than for any other race-gender group. For religiosity, however, we find little evidence that risk is related to religiosity among Black women, while highly correlated with white women's religious engagement. For men—whether Black or white—risk exhibits a modest, positive relationship with their religiosity. Our results speak to the importance of considering intersectionality and race-gender identities in evaluations of religious and political activities in the United States.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 it