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Record W2905098799 · doi:10.1080/07303084.2018.1535338

Strategies for Teaching Children with Autism Spectrum Disorder in Recreational Aquatics Programs

2018· article· en· W2905098799 on OpenAlexaff
Erin Kraft, Raymond Leblanc, Diane M. Culver

Bibliographic record

VenueJournal of Physical Education Recreation & Dance · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicInclusion and Disability in Education and Sport
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsRecreationAutism spectrum disorderAutismPsychologyDevelopmental psychologyBiology

Abstract

fetched live from OpenAlex

With the increase in the identification of autism spectrum disorder (ASD) in children, there is a need for teachers and coaches to have a tool box of effective strategies to facilitate physical activities for their students with ASD. Physical activity has been shown to provide numerous benefits, such as improved resilience and enhanced positive development. Swimming, specifically, is an optimal form of physical activity for children with ASD and an important life skill, considering that drowning is a leading cause of death among children with ASD. Training programs and educational opportunities for accessing appropriate strategies to teach children with ASD are seemingly scarce. This article aims to minimize this lack of resources by suggesting hands-on teaching strategies for aquatic programs for children with ASD to enhance the swimmers' opportunities to participate in recreational aquatic activities.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.544
Threshold uncertainty score0.359

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.015
GPT teacher head0.364
Teacher spread0.350 · 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 designTheoretical or conceptual
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

Citations9
Published2018
Admission routes1
Has abstractyes

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