Learning life skills through high school football: Athletes' perspective on the role of coaches
Bibliographic record
Abstract
Organisations governing the practice of high school sport in Canada communicate through their mission statement that sport is a viable setting in which to promote the positive development of students (Camire, Werthner, & Trudel, 2009). In recent years, there has been a proliferation of football programs in the province of Quebec and the sport is often seen as a valuable tool to motivate boys, who have the highest dropout rate in the country, to remain in school (Richards, 2012). However, research findings indicate thatsport is not a panacea and cannot automatically prevent students from dropping out of school (Danish & Nellen, 1997). Rather, it is the quality of the relationship formed with coaches that is most likely to lead to positive developmental outcomes (Petitpas et al., 2005).The purpose of this study was to document athletes' perspective on life skill development through football and the role played by coaches in promoting positive development. Eighteen male high school football players from Quebec participated in focus groups ranging from 37 to 49 minutes (M = 45). Results demonstrate that participants believe they learned a number of life skills such as leadership, teamwork, and emotional control through football. Participants also acknowledged that coaches played a key role in their development as they made intentional efforts to nurture quality relationships with players and used a number of strategies to promote the learning of life skills. Results are discussed using the positive youth development through sport literature.Acknowledgments: This study was supported by a grant from SSHRC.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".