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Record W2763408295 · doi:10.1111/jar.12414

Patterns of sport participation for youth with autism spectrum disorder and intellectual disabilities

2017· article· en· W2763408295 on OpenAlexafffund
Stephanie Ryan, Jessica Fraser‐Thomas, Jonathan A. Weiss

Bibliographic record

VenueJournal of Applied Research in Intellectual Disabilities · 2017
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsYork University
FundersCanadian Institutes of Health ResearchHealth CanadaSinneave Family FoundationAutism Speaks
KeywordsIntellectual disabilityAutism spectrum disorderPsychologyMediationDiversity (politics)AutismDevelopmental psychologyClinical psychologyTypically developingPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Little is known about sport participation in youth with Autism Spectrum Disorder (ASD). The current study examined sport characteristics (frequency, diversity, positive social experiences [PSE]) for youth with ASD and intellectual disability compared to youth with intellectual disability alone and explored the personal and contextual correlates of involvement. METHOD: Parents (N = 409) completed an online survey, and multiple mediation analyses were used to examine the factors that explained the relationships between sport involvement in youth with ASD and intellectual disability. RESULTS: No significant main effects of ASD status were found for frequency or diversity, but youth with intellectual disability alone had higher scores for PSE compared to youth with ASD and intellectual disability. Sociocommunicative abilities, coach relationship and resources mediated the relationship between ASD status and PSE. CONCLUSIONS: A better understanding of the factors related to sport is essential for allowing families, service providers and policy makers to improve involvement for youth with ASD.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.130
GPT teacher head0.382
Teacher spread0.252 · 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

Citations35
Published2017
Admission routes2
Has abstractyes

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