Paid Maternity Leave and Breastfeeding in Urban China
Bibliographic record
Abstract
Using data from the 2010 Survey on Chinese Women's Social Status, this contribution estimates the effect of paid maternity leave on breastfeeding duration in urban China during the 1988–2008 period. The analysis applies a policy-based identification strategy to control for the endogenous relationship between paid leave entitlements and breastfeeding decisions. Estimates show that paid maternity leave has a strong positive effect on breastfeeding duration. Specifically, if the length of paid leave increases by thirty days, then the probability of breastfeeding for at least six months increases by 12 percentage points. Between 1988 and 2008, the average length of paid leave for mothers without a college education decreased by twenty-three days, which reduced these mothers’ probability of breastfeeding for at least six months by 9 percentage points. These results support the view that paid maternity leave enhances the ability of employed women to sustain breastfeeding and call for universal paid leave entitlements.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".