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Record W2621357550 · doi:10.18666/trj-2017-v51-i2-7383

Examining the Impact of a Multi-Sport Camp for Girls Ages 8–11 With Autism Spectrum Disorder

2017· article· en· W2621357550 on OpenAlexaff
Lindsay M. Guest, Robert Balogh, Shilpa Dogra, Meghann Lloyd

Bibliographic record

VenueTherapeutic Recreation Journal · 2017
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsRecreationPsychologyAutism spectrum disorderSocial skillsIntervention (counseling)AutismDevelopmental psychologyMotor skillPerceptionClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Research on Autism Spectrum Disorder (ASD) has increased significantly over the past decade; however, rarely does research focus solely on girls with ASD. Girls with ASD are more likely to have less proficient motor skills than both their peers with typical development, and boys with and without ASD. This further discourages participation in sport, recreation, and leisure activities and deprives the opportunity to develop social skills among peers; both of which are primary goals of therapeutic recreation. The purpose of this study was to examine the impact of a multi-sport camp intervention aimed at improving motor skills, physical activity levels, physical self-perceptions, and adaptive behaviour of 13 girls with ASD between the ages of 8 to 11. Results indicated that the camp was effective at improving motor skills (p<0.0001), physical self-perceptions (p=0.044) and social skills (p=0.005); however, further research with larger samples and a longer duration of intervention is necessary.

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 score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.114
GPT teacher head0.382
Teacher spread0.269 · 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

Citations45
Published2017
Admission routes1
Has abstractyes

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