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Record W2767288802 · doi:10.1080/13545701.2017.1380309

Paid Maternity Leave and Breastfeeding in Urban China

2017· article· en· W2767288802 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFeminist Economics · 2017
Typearticle
Languageen
FieldMedicine
TopicBreastfeeding Practices and Influences
Canadian institutionsUniversity of Winnipeg
FundersInternational Labour OrganizationNational Natural Science Foundation of China
KeywordsBreastfeedingChinaMaternity leaveSocioeconomicsDemographic economicsEconomic growthGeographyMedicineSociologyEconomicsPediatrics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.464

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.278
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it