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Record W6950743923 · doi:10.5683/sp3/t44xfz

Enquête canadienne sur l’apprentissage et la garde des jeunes enfants, 2023 [Canada]

2025· dataset· fr· W6950743923 on OpenAlexaboutno aff

Bibliographic record

VenueBorealis · 2025
Typedataset
Languagefr
FieldMedicine
TopicFetal and Pediatric Neurological Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsIdentity (music)Context (archaeology)Child careGender identity

Abstract

fetched live from OpenAlex

Des questions sont posées aux parents et aux tuteurs au sujet des modes d'apprentissage et de garde utilisés pour leur enfant de 0 à 5 ans, y compris les coûts associés et les difficultés qui ont possiblement été rencontrées lors de la recherche d'un service de garde, et de leurs préférences en ce qui concerne la garde des enfants. L'enquête permet aussi de recueillir des renseignements sur la participation au marché du travail des parents et des tuteurs afin de mieux comprendre les interactions entre le travail et l'utilisation des modes d'apprentissage et de garde des jeunes enfants. Les résultats de cette enquête serviront à améliorer le système pancanadien d'apprentissage et de garde des jeunes enfants et fourniront aux Canadiens des données de base solides afin de mesurer le progrès du système et les changements qui y sont apportés.

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)0.003
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.170
Threshold uncertainty score0.342

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0060.009
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0030.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0220.022

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 head0.012
GPT teacher head0.250
Teacher spread0.237 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueBorealisSame topicFetal and Pediatric Neurological DisordersFrench-language works237,207