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Record W7100954857

Cahier de recherche/Working Paper No. 119 The Effect of Childcare and Early Education Arrangements on Developmental Outcomes

2000· article· en· W7100954857 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsnot available
Fundersnot available
KeywordsChild developmentEarly childhood educationChild rearingPre schoolSocial environment
DOInot available

Abstract

fetched live from OpenAlex

acknowledged. Résumé: Cette étude explore la relation entre les modalités des services de garde et des indicateurs mesurés du développement des jeunes enfants à l’aide des données du cycle 1 de l’Enquête longitudinale nationale sur les enfants et les jeunes canadiens. La modélisation économétrique analyse les déterminants des scores de développement social et moteur (DSM) des enfants de 0 à 47 mois ainsi que les scores à un test de vocabulaire (EVIP-R) administré aux enfants de 4-5 ans en prenant en considération différentes caractéristiques des services de garde et d’éducation des enfants. Les résultats suggèrent que pour les nouveaux-nés et les enfants en bas âge les modalités de garde non parentale ont des effets non statistiquement significatifs ou négligeables sur le DSM. Pour les enfants d’âge préscolaire, les modes de garde ou d’éducation préscolaire n’ont pas en moyenne d’effets sur le développement cognitif (EVIP). L’estimation d’un modèle à effets fixes pour un sous-échantillon d’enfants composé de frères et de sœurs confirme la conclusion précédente. L’analyse est répétée pour identifier les déterminants de la probabilité qu’un enfant soit observé avec un score le classant dans la partie inférieure de la distribution des scores (DSM et EVIP), et les conclusions sont similaires.

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)0.016
metaresearch head score (Gemma)0.044
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.110
Threshold uncertainty score0.368

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.044
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.007
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.1100.024

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 head0.040
GPT teacher head0.352
Teacher spread0.313 · 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
Published2000
Admission routes1
Has abstractyes

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