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Record W4413902513 · doi:10.1123/apaq.2024-0141

A Competency-Based Analysis of Provider Training at Community-Based Exercise Programs for Persons With Disabilities Across Canada: An Environmental Scan

2025· article· en· W4413902513 on OpenAlexaffabout
Alexandra J. Walters, Norman Ng, Amy E. Latimer‐Cheung, Jennifer R. Tomasone

Bibliographic record

VenueAdapted Physical Activity Quarterly · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicInclusion and Disability in Education and Sport
Canadian institutionsQueen's University
Fundersnot available
KeywordsOnboardingMedical educationPsychologyTraining (meteorology)MedicineSocial psychology

Abstract

fetched live from OpenAlex

Many qualified exercise professionals are underprepared to support the quality exercise experiences of persons with disabilities. Community-based exercise programs for persons with disabilities often offer new providers (i.e., staff, volunteers, and students) specialized onboarding training. We aimed to identify the competency elements delivered in these trainings. Applying a competency-based lens, training materials (n = 94) from community-based exercise programs in Canada (n = 9) were analyzed to identify competency elements (i.e., knowledge, skills, and attitudes) taught to providers and differences in training content between provider types. The majority of training content focused on the provision of knowledge, with less attention to skills and attitudes training. Focusing on knowledge acquisition can leave providers without the capacity to apply the knowledge they have attained in real-time situations. Staff training was oriented toward disability-specific content, while volunteer and student training focused more on general and program-specific content. Findings informed the development of disability-specific competencies for qualified exercise professionals in community exercise settings.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.036
GPT teacher head0.330
Teacher spread0.294 · 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.

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

Citations2
Published2025
Admission routes2
Has abstractyes

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Same venueAdapted Physical Activity QuarterlySame topicInclusion and Disability in Education and SportFrench-language works237,207