MétaCan
Menu
Back to cohort
Record W2889717991 · doi:10.3138/cpp.39.2.263

New Evidence on the Impacts of Access to and Attending Universal Child-Care in Canada

2013· article· en· W2889717991 on OpenAlexaffvenueabout
Michael J. Kottelenberg, Steven Lehrer

Bibliographic record

VenueCanadian Public Policy · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsQueen's University
Fundersnot available
KeywordsAttendanceChild careCriticismPsychologyTest (biology)Robustness (evolution)MedicinePublic economicsNursingPolitical scienceEconomic growthEconomics

Abstract

fetched live from OpenAlex

In Canada, advocates of universal child-care often point to policies implemented in Quebec as providing a model for early education and care policies in other provinces. While these policies have proven to be highly popular among citizens, initial evaluations of access to these programs indicated they led to a multitude of undesirable child developmental, health, and family outcomes. These research findings ignited substantial controversy and criticism. In this study, we show the robustness of the initial analyses to 1) concerns over whether negative outcomes would vanish over time as suppliers gained experience providing child-care; 2)concerns regarding multiple testing; and 3) concerns that the original estimates measured the causal impact of child-care availability and not child-care attendance. A notable exception is that despite estimated effects stemming from the policy indicating declines in motor-social development scores in Quebec relative to the rest of Canada, our analyses imply that on average attending child-care in Canada leads to a significant increase in this test score. However, our analysis reveals substantial heterogeneity in program impacts that occur in response to the Quebec policies and indicates that most of the negative impacts reported in earlier research are driven by children from families who only attended child-care in response to the implementation of this policy.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.391
Threshold uncertainty score0.926

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.036
GPT teacher head0.299
Teacher spread0.264 · 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

Citations53
Published2013
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Public PolicySame topicEarly Childhood Education and DevelopmentFrench-language works237,207