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Record W7096486698

Child-Care Policy and the Labor Supply of Mothers with Young Children: A Natural Experiment

2015· article· en· W7096486698 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsnot available
Fundersnot available
KeywordsMicrodata (statistics)Natural experimentGovernment (linguistics)Descriptive statisticsCensusSurvey data collectionHousehold incomeOfficial statistics
DOInot available

Abstract

fetched live from OpenAlex

In 1997, the provincial government of Québec, the second most pop-ulous province in Canada, initiated a new child-care policy. Licensed child-care service providers began offering day-care spaces at the reduced fee of $5.00 per day per child for children aged 4. By 2000, the policy applied to all children not in kindergarten. Using annual data (1993–2002) drawn from Statistics Canada’s Survey of Labour and Income Dynamics, the results show that the policy had a large and statistically significant impact on the labor supply of mothers with preschool children. This analysis is based on Statistics Canada’s Survey of Labor and Income Dy-namics (SLID) restricted-access annual (1993–2002) Microdata Files, which con-tain anonymized data collected in the SLID. The data are available at the Québec Inter-university Center for Social Statistics (QICSS), a center of the Canadian Research Data network. Pierre Lefebvre and Philip Merrigan prepared all com-putations on these microdata. The responsibility for the use and interpretation of these data is entirely ours. This research was partly funded by CIRANO-

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.148
Threshold uncertainty score0.294

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0090.002

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 head0.007
GPT teacher head0.276
Teacher spread0.269 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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