A Competency-Based Analysis of Provider Training at Community-Based Exercise Programs for Persons With Disabilities Across Canada: An Environmental Scan
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".