Do Targeted Stipend Programs Reduce Gender and Socioeconomic Inequalities in Schooling Attainment? Insights From Rural Bangladesh
Why this work is in the frame
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Bibliographic record
Abstract
Social investment in schooling in low-income countries has increased greatly in the 1990s and 2000s because of the robust associations among schooling and demographic, economic, and health outcomes. This analysis investigates whether targeted school-attendance stipend programs succeeded in reducing gender and socioeconomic inequalities in school attainment among a sample of the rural poor in Bangladesh. Multivariate analyses find that targeted stipend programs helped to reduce the gender attainment gap. Females had an increased probability of participating in stipend programs, and returns to stipend participation were significantly higher for females. However, stipend programs failed to reduce the relative achievement gap between children of different socioeconomic backgrounds: low socioeconomic status (SES) was associated with a decreased probability of stipend participation, and stipend-related schooling gains for lower-SES females were matched by comparable gains for higher-SES females. Meanwhile, there was no significant association between stipend participation and schooling attainment for males.
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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) | 0.000 | 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