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Record W4385429745 · doi:10.1080/1612197x.2023.2242375

Parent–child co-participation in sport and physical activity: a scoping review

2023· review· en· W4385429745 on OpenAlexafffund
Haley Hunter Smith, Jean Côté

Bibliographic record

VenueInternational Journal of Sport and Exercise Psychology · 2023
Typereview
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsQueen's University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyContext (archaeology)Physical activityProcess (computing)Peer reviewSocial psychologyDevelopmental psychologyPolitical science

Abstract

fetched live from OpenAlex

Parent–child co-participation has often been correlated with physical activity engagement levels. However, both new research and anecdotal evidence suggest that parent–child sport co-participation may provide developmental benefits for both parents and their children beyond simple rates of engagement. The aims of this scoping review were twofold: first, to gather the available research on parent–child co-participation in the sport context and identify how co-participation has been conceptualised in the literature, and second, to discuss the contexts in which parent–child co-participation has been investigated. Through this review, we found that co-participation has most often been conceptualised as either a predictor of physical activity or a one-dimensional outcome variable. A small number of studies have examined co-participation as a developmental process. Future research recommendations include examining co-participation in greater detail as a process, with the intent to further understand the developmental contexts of these sport and relationship environments.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.952
Threshold uncertainty score0.710

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.122
GPT teacher head0.509
Teacher spread0.387 · 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 designOther design
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

Citations11
Published2023
Admission routes2
Has abstractyes

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