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Record W2170401282 · doi:10.1093/cesifo/ifu006

Do the Perils of Universal Childcare Depend on the Child's Age?

2014· article· en· W2170401282 on OpenAlexafffundabout
Michael J. Kottelenberg, Steven Lehrer

Bibliographic record

VenueCESifo Economic Studies · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsQueen's University
FundersSocial Sciences and Humanities Research Council of CanadaYork UniversityUniversity of Ottawa
KeywordsSubsidyPsychologyDevelopmental psychologyEconomics

Abstract

fetched live from OpenAlex

The rising participation of women in paid work has not only heightened demand for universal early education and care programs but also led to increased use of childcare amongst children at earlier ages. Prior research investigating Quebec’s universal highly subsidized childcare documented significant declines in a variety of developmental outcomes for all children aged 0–4 years. However, past analysis has not explored whether these effects vary for children of different ages. In this article, we demonstrate substantial heterogeneity in policy impacts by child age. Children who gain access to subsidized childcare at earlier ages experience significantly larger negative impacts on developmental scores, health, and behavioral outcomes. The sole exception is the negative relationship between access to subsidized childcare and hyperactivity scores which steepens with child age. Our analysis additionally provides significant evidence of treatment effect heterogeneity within ages, and reveals benefits from access to universal childcare on developmental scores for those that are above 3 years of age.

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)0.004
metaresearch head score (Gemma)0.019
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 score0.193
Threshold uncertainty score0.384

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.031
GPT teacher head0.270
Teacher spread0.239 · 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

Citations53
Published2014
Admission routes3
Has abstractyes

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