Explaining religious differentials in family-size preference: Evidence from Nepal in 1996
Why this work is in the frame
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Bibliographic record
Abstract
We examine how religio-ethnic identity, individual religiosity, and family members' religiosity were related to preferred family size in Nepal in 1996. Analyses of survey data from the Chitwan Valley Family Study show that socio-economic characteristics and individual experiences can suppress, as well as largely account for, religio-ethnic differences in fertility preference. These religio-ethnic differentials are associated with variance in particularized theologies or general value orientations (like son preference) across groups. In addition, individual and family religiosity are both positively associated with preferred family size, seemingly because of their association with religious beliefs—beliefs that are likely to shape fertility strategies. These findings suggest the need for improvements in how we conceptualize and measure supra-individual religious influence in a variety of settings and for a range of demographically interesting outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it