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Record W3209650261 · doi:10.1123/cssep.2021-0016

Experiencing the Social Environment of a Canoe Kayak Club: A Case Study of a Special Olympics Program

2021· article· en· W3209650261 on OpenAlexaff
Krystn Orr, M. Blair Evans, Katherine A. Tamminen, Kelly P. Arbour‐Nicitopoulos

Bibliographic record

VenueCase Studies in Sport and Exercise Psychology · 2021
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsHolland Bloorview Kids Rehabilitation HospitalWestern UniversityUniversity of TorontoMcMaster University
Fundersnot available
KeywordsCoachingClubAthletesVideographyPsychologyIntellectual disabilityAutism spectrum disorderApplied psychologyQualitative researchMedical educationDevelopmental psychologyAutismAdvertisingMedicineSociologyPsychiatry

Abstract

fetched live from OpenAlex

For individuals with an intellectual disability, emerging adulthood (18–25 years) may be a disruptive time with an abrupt ending to programming and services after adolescence. This study critically explores the social environment and experiences of individuals involved in a Special Olympics paddling program for emerging adult athletes with an intellectual disability. Using an instrumental case study design, multiple qualitative methods were implemented including photography, videography, observations, and interviews. The participants included four athletes (one female and three male; three with autism spectrum disorder, one with mild intellectual disability), three fathers, a coach, a program coordinator, and an administrator. Analyses were guided by interpretivism and the quality parasport participation framework. The findings highlight how the limited staff training and preparation, the complexity of providing such a program, and parental hidden labor in their adult children’s sport involvement influence the social environment. Implications for coaching practices include the importance of communication strategies and coach education.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.442
Threshold uncertainty score0.536

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 studies0.0010.000
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 head0.144
GPT teacher head0.512
Teacher spread0.368 · 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 designQualitative
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

Citations1
Published2021
Admission routes1
Has abstractyes

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