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Record W4416426650 · doi:10.1123/kr.2025-0047

Codevelopment of Movement Competence and Executive Function in Childhood: A Roadmap Toward a Bioecologically Grounded Mixed-Methods Approach

2025· article· W4416426650 on OpenAlexaff
Simon Schaerz

Bibliographic record

VenueKinesiology Review · 2025
Typearticle
Language
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsLethbridge CollegeUniversity of Lethbridge
Fundersnot available
KeywordsCompetence (human resources)Function (biology)Movement (music)Qualitative researchQualitative propertyGrounded theory

Abstract

fetched live from OpenAlex

Movement competence (MC) and executive function (EF) are tightly interwoven developmental domains, each shaping and being shaped by the other throughout childhood, yet most research relies on decontextualized assessments and rarely examines the lived experiences that shape development. The purpose of this article is to outline a bioecologically grounded, mixed-methods roadmap for studying MC–EF codevelopment. Guided by Bronfenbrenner’s bioecological model, the roadmap integrates dynamic MC assessments, psychometric and behavioral EF measures, and qualitative insights from children and caregivers. An explanatory sequential design links quantitative classification of MC–EF profiles with in-depth qualitative exploration of movement experiences, child characteristics, and contextual influences, supported by joint display integration. A longitudinal extension captures how these processes evolve across seasonal and multiyear timescales. By situating MC–EF development within its real-world bioecology, this roadmap offers researchers and practitioners a flexible yet rigorous model for advancing both theory and application in the exercise-cognition field.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.937
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.023
GPT teacher head0.328
Teacher spread0.305 · 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
GenreReview

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

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