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Record W2788656806 · doi:10.1352/1944-7558-123.2.164

Individual and Contextual Correlates of Frequently Involved Special Olympics Athletes

2018· article· en· W2788656806 on OpenAlexafffund
Suzanne Robinson, Jessica Fraser‐Thomas, Robert Balogh, Yona Lunsky, Jonathan A. Weiss

Bibliographic record

VenueAmerican Journal on Intellectual and Developmental Disabilities · 2018
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsCentre for Addiction and Mental HealthOntario Tech UniversityYork University
FundersCanadian Institutes of Health Research
KeywordsAthletesPsychologyYouth sportsIntellectual disabilitySample (material)Developmental psychologyMedicinePhysical therapyPsychiatry

Abstract

fetched live from OpenAlex

It is important to understand factors associated with sport participation for youth with intellectual and developmental disabilities (IDD). With a sample of 414 Special Olympics (SO) athletes, this study examined how frequently involved athletes differ from other youth who are less involved in SO. Results showed that frequently involved athletes are older, have more sport-specific parental support, stronger athlete-coach relationships, and more positive SO experiences than other athletes. These factors were predictive of SO involvement, even after controlling for athlete characteristics, including behavior problems and adaptive behavior. Athletes with IDD have the potential to be highly involved in sports when external supports (i.e., coaches and parents) are strong.

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)0.003
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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.047
GPT teacher head0.307
Teacher spread0.261 · 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

Citations15
Published2018
Admission routes2
Has abstractyes

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Same venueAmerican Journal on Intellectual and Developmental DisabilitiesSame topicFamily and Disability Support ResearchFrench-language works237,207