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Record W3208078923

Utilizing Knowledge Translation to Enhance Quality Participation in Recreational Sport Programming for Children with Intellectual and Developmental Disabilities

2021· article· en· W3208078923 on OpenAlexaboutno aff
Natasha Bruno, Jennifer R. Tomasone, Kelly P. Arbour‐Nicitopoulos, Tom Davies, Amy E. Latimer‐Cheung

Bibliographic record

VenueQSpace (Queen's University Library) · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicInclusion and Disability in Education and Sport
Canadian institutionsnot available
Fundersnot available
KeywordsKnowledge translationBlueprintContext (archaeology)RecreationPublic relationsPsychologyQuality (philosophy)Medical educationBest practiceKnowledge managementPolitical scienceMedicineEngineeringComputer science
DOInot available

Abstract

fetched live from OpenAlex

For children with an intellectual and developmental disability (IDD), meaningful inclusion in sport can lead to many physical and psychosocial benefits such as improved motor skills, self-esteem, and social skills. Accordingly, investigators have begun to explore the ways in which sport participation environments should be designed and programs be implemented to promote these valued outcomes for children with IDD. Despite advancements in disability sport research, program providers are not always equipped with the knowledge and resources to ensure they are meeting the needs and participation priorities of children with IDD. To address these needs, our team partnered with Special Olympics Canada – the largest national organization dedicated to providing sport opportunities to persons with IDD – to encourage high-quality, evidence-based sport programming across Canada for children with IDD. Specifically, we engaged in an integrated knowledge translation process to apply and mobilize quality participation evidence to improve the sport experiences of children with IDD participating in Special Olympics Canada Active Start (i.e., ages 2-6 years) and Fundamentals (i.e., ages 7-12 years) sport programs. Informed by the knowledge-to-action framework’s eight-phase action cycle, my thesis work adapted the Canadian Disability Participation Project’s Blueprint for Building Quality Participation to Special Olympics Canada’s context using evidence from a related systematic scoping review as well as insights from Special Olympics Canada provincial Youth Development Coordinators, and Active Start and FUNdamentals program leader training materials. Succeeding this, I assessed the perceived barriers and facilitators of the adapted quality participation knowledge tool from the perspectives of provincial Youth Development Coordinators. Based on their feedback, two quality participation knowledge tools resulted: (1) the Special Olympics Canada Blueprint for program leader education and (2) the Special Olympics Canada Special Olympics Canada Program Audit and Improvement Tool for program leader self-reflection. Key findings and lessons learned for adapting, assessing and tailoring knowledge are presented to guide future integrated knowledge translation partnerships. By elucidating the phases of the action cycle, we hope to encourage future initiatives geared towards translating knowledge into action in the field of disability and sport.

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)0.130
metaresearch head score (Gemma)0.189
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.130
Threshold uncertainty score0.687

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1300.189
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0080.007
Science and technology studies0.0060.006
Scholarly communication0.0120.008
Open science0.0050.017
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0070.001

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 head0.037
GPT teacher head0.326
Teacher spread0.289 · 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 designNot applicable
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

Citations0
Published2021
Admission routes1
Has abstractyes

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Same venueQSpace (Queen's University Library)Same topicInclusion and Disability in Education and SportFrench-language works237,207