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Record W4212888351 · doi:10.1080/03004430.2022.2042279

Children’s engagement in Quebec childcare centres: progression from 3 to 5 years old and predictor variables

2022· article· en· W4212888351 on OpenAlexafffundabout
Maude Roy-Vallières, J.M. Lachapelle, Lise Lemay, Caroline Bouchard, Nathalie Bigras

Bibliographic record

VenueEarly Child Development and Care · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsUniversité LavalUniversité du Québec à Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyContext (archaeology)Socioeconomic statusDevelopmental psychologyStudent engagementConstruct (python library)Longitudinal studyDemographySociologyPopulationGeographyPedagogyMedicine

Abstract

fetched live from OpenAlex

This study examined the longitudinal evolution of 3 to 5 year old children's level of engagement in Quebec's early childcare centres. A latent transition analysis was conducted on child engagement measured by the inCLASS. Results revealed three engagement profiles at ages 3 and 5: 1) low engagement profile; 2) low- medium engagement profile; 3) medium engagement profile, suggesting a generally positive but low engagement. The study also identified that over 80% of children, regardless of profile at age 3, transition to the medium engagement profile by age 5. Various predictor variables were explored to explain this transition with socioeconomic context of the child's family at age 5 found to be the sole predictive variable, suggesting a strong impact of family context on children’s engagement. This suggests that engagement is a distinct construct from the wider educational quality concept, modulated by child-specific characteristics. Implications for research and educational practice are discussed.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.117
Threshold uncertainty score0.236

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.008
GPT teacher head0.244
Teacher spread0.236 · 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

Citations2
Published2022
Admission routes3
Has abstractyes

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