Son-Preference, Gender Difierentials in Child Labor and Schooling, and E-ciency
Bibliographic record
Abstract
This paper studies the efiects of son-preference by parents on child labor and schooling in a model with bilateral altruism between parents and children. The results suggest that son-preference leads to a gender difierential in child labor with female children working more than male children. But, it does not lead to a gender difierential in schooling. Only when parents cannot give bequests, female children receive less schooling than male children. Binding bequest constraint results in an ine‐ciently high level of child labor and a low level of schooling. Reverse transfers (transfers from children to parents) in the second period result in ine‐ciently high level of schooling and low level of child labor, a result which is in contrast to models of Baland and Robinson (2000) and Horowitz and Wang (2004). The empirical evidence from rural areas of Bangladesh shows that son-preference is an important factor explaining the observed gender difierential in child labor.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".