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Record W3039510801 · doi:10.4102/sajce.v10i1.803

Preschool cognitive control and family adversity predict the evolution of classroom engagement in elementary school

2020· article· en· W3039510801 on OpenAlexaffabout
Caroline Fitzpatrick, Isabelle Archambault, Tracie A. Barnett, Linda S. Pagani

Bibliographic record

VenueSouth African Journal of Childhood Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsInstitut National de la Recherche ScientifiqueUniversité de MontréalUniversité Sainte-Anne
Fundersnot available
KeywordsPsychologyDevelopmental psychologyHostilityImpulsivityContext (archaeology)CognitionAcademic achievementCognitive developmentChild developmentParenting stylesClinical psychology

Abstract

fetched live from OpenAlex

Background: Classroom engagement is key predictor of child academic success.Aim: The objective of the study was to examine how preschool cognitive control and the experience of family adversity predict developmental trajectories of classroom engagement through elementary school.Setting: Children were followed in the context of the Quebec Longitudinal Study of Child Development from birth to age 10.5 (N = 1589).Methods: Working memory was directly assessed when children were 3 years old and mothers reported child impulsivity, parenting characteristics, stress and social support when children were 4 years old. Elementary school teachers rated classroom engagement from kindergarten through Grade 4.Results: Growth mixture modelling identified three distinct trajectories of classroom engagement. Child working memory and impulsivity, and maternal hostility, social support and stress predicted greater odds of belonging to the low versus high engagement trajectory. Child impulsivity and maternal hostility and stress also distinguished between the low and moderate engagement trajectories.Conclusion: Our results suggest that targeting preschool cognitive control and buffering the effects of family adversity on children may facilitate academic success.

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)0.001
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 score0.017
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.011
GPT teacher head0.247
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 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

Citations6
Published2020
Admission routes2
Has abstractyes

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