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Record W4295760963 · doi:10.1080/00221325.2022.2121638

Child Cognitive Flexibility and Maternal Control: A First Step toward Untangling Genetic and Environmental Contributions

2022· article· en· W4295760963 on OpenAlexaff
Frédéric Thériault‐Couture, Célia Matte‐Gagné, Samuel Dallaire, Mara Brendgen, Frank Vitaro, Richard E. Tremblay, Jean R. Séguin, Ginette Dionne, Michel Boivin

Bibliographic record

VenueThe Journal of Genetic Psychology · 2022
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversité de MontréalUniversité du Québec à MontréalCentre Hospitalier Universitaire Sainte-JustineUniversité Laval
Fundersnot available
KeywordsFlexibility (engineering)Cognitive flexibilityCognitionDevelopmental psychologyPsychologyTask (project management)Bivariate analysisExecutive functionsBehavioural geneticsComputer sciencePsychiatry

Abstract

fetched live from OpenAlex

Executive functions (EF) play an essential role in many spheres of child development. Therefore, it is crucial to get a better understanding of their etiology. Using a genetic design that involved 934 twins (400 monozygotic), this study examined the etiology of cognitive flexibility, a component of EF, at 5 years of age and its phenotypic and etiological associations with maternal control. Cognitive flexibility was measured in a laboratory setting at 5 years of age using a well-known EF-task, i.e. the Dimensional Change Card Sort (DCCS). Maternal control was measured using a self-report questionnaire. The univariate genetic model demonstrated that environmental factors mainly explained individual differences in preschoolers’ performance on the DCCS task. A bivariate genetic model demonstrated that non-shared environmental mechanisms mainly explained the association (r = .−13) between maternal control and children’s performance on the DCCS task. This study represents a preliminary step toward a better understanding of the genetic and environmental contributions underlying the relation between parenting behaviors and children’s EF.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.277
Teacher spread0.263 · 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 routes1
Has abstractyes

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