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Record W3122360623

Canadian Evidence on Ten Years of Universal Preschool Policies: the Good and the Bad

2013· preprint· en· W3122360623 on OpenAlexaffabout
Catherine Haeck, Pierre Lefèbvre, Philip Merrigan

Bibliographic record

VenueRePEc: Research Papers in Economics · 2013
Typepreprint
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsCognitionCognitive developmentChild developmentEconomicsDemographic economicsPsychologyEconomic growthMedicineDevelopmental psychology
DOInot available

Abstract

fetched live from OpenAlex

More than ten years ago, to increase mothers’ participation in the labour market and to enhance child development, the province of Québec implemented a $5 per day universal childcare policy. This paper provides a comprehensive review of the costs and benefits of the program over that period. A non-experimental evaluation framework based on multiple pre- and post-treatment periods is used to estimate the policy effects. We find that the reform had important and lasting effects on the number of children aged 1 to 4 attending childcare and the numbers of hours they spend in daycare. For children aged 5, we uncovered strong evidence that implementing full-day kindergarten alone was not enough to increase maternal labour force participation and weeks worked, but when combined with the low-fee daycare program it was, and these effects were also long lasting. Our results on cognitive development suggest that the school setting is more successful in raising children’s cognitive ability than the daycare setting. Finally, we show that the fiscal costs were most likely larger than the benefits.

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 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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.427
Threshold uncertainty score0.664

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.031
GPT teacher head0.311
Teacher spread0.280 · 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 teacher head, 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

Citations3
Published2013
Admission routes2
Has abstractyes

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