Social and environmental factors affecting the learning and acquisition of knowledge among youth disability sport coaches
Bibliographic record
Abstract
Nearly 5% of Canadian youth reported living with a physical disability (Employment and Social Development Canada, 2006). These youth are less likely to be physically active compared to youth without an impairment, which in turn affects their health and quality of life. Having youth with physical disabilities engaged in sport constitutes a way to increase their level of physical activity and improve their health. The acquisition of these benefits can be facilitated by the presence of trained and skilled coaches. The purpose of the study was to gain an understanding of the learning experiences and acquisition of knowledge of youth disability sport coaches. Five experienced youth disability sport coaches participated in individual interviews and the data were analyzed using a hierarchical content analysis. The inductive analysis revealed that the content of their learning was affected by various social and environmental factors such as their sporting background, access to coach certification, lack of financial resources, limited pool of players, poor sport promotion, and the individuals surrounding the youth disability sport environment. The current findings are of interest to coaches in youth disability sport since most research in this area has focused on elite or Paralympic coaches. Moreover, these results raise awareness of effective coaching practices in youth disability sport by providing direction and guidance on ways of acquiring this information. In fact, having more skilled coaches would enhance the sport experience of youth athletes with a disability, and hopefully encourage them to get more involved in sport.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".