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Record W4377241879 · doi:10.1177/08295735231173518

Motor Skills are More Strongly Associated to Academic Performance for Girls Than Boys

2023· article· en· W4377241879 on OpenAlexaff
Eda Çınar, Caroline Fitzpatrick, Maíra Lopes Almeida, Chantal Camden, Gabrielle Garon‐Carrier

Bibliographic record

VenueCanadian Journal of School Psychology · 2023
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsCentre Hospitalier Universitaire de SherbrookeUniversité de Sherbrooke
Fundersnot available
KeywordsPsychologyGross motor skillDevelopmental psychologyMotor skillCognitive skillVocabularyCognitionAcademic achievementAssociation (psychology)NumeracyAttentional controlLiteracyNeurosciencePedagogy

Abstract

fetched live from OpenAlex

This study investigated the contribution of fine and gross motor skills to academic and attentional performance at school entry among 832 boys and girls. Children were tested on their fine and gross motor skills (locomotor, object control) and their academic performance in receptive vocabulary, number knowledge, and attentional skills at 6 to 7 years old. Results from ordinary least square models adjusted for family income, maternal education attainment, and early cognitive skills at 41 to 48 months revealed that fine motor skills significantly predicted receptive vocabulary, number knowledge, and attention skills. The associations between fine motor skills with receptive vocabulary and attention were stronger for girls than boys. Better performance in locomotor also significantly predicted higher levels of receptive vocabulary while object control was positively associated with attentional skills among girls only. Children with better motor abilities, especially fine motor skills, are more likely to be successful in the areas requiring language, numeracy, and attentional skills. Thus, motor skills should be a focus of interest for increasing academic and attentional skills level at school entry, particularly in girls.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.518
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.031
GPT teacher head0.330
Teacher spread0.298 · 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.

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

Citations19
Published2023
Admission routes1
Has abstractyes

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