The Influence of Coaches' Life Experience on Sport-Based Youth Development Programming
Bibliographic record
Abstract
Researchers have examined the role of youth sport coaches in facilitating Sports-based Youth Development (SBYD) programs to reveal that an intentional approach to development from coaches can play an important part in the development of young people into thriving adults. However, little is known about the relationship between coach intentions and developmental outcomes through SBYD programs for youth from low socio-economic status neighbourhoods (side-lined youth). This study explores the coaching approaches of 9 coaches who facilitate SBYD programming for side-lined youth in the Greater Toronto Area (GTA). Nine SBYD coaches (4 males ages 25-50 and 5 females ages 26-39) were interviewed to gain a deeper understanding of coach approaches to the development of side-lined youth through sport. A thematic analysis revealed a difference of perspectives on the intentions towards development between coaches with lived experiences (i.e., facilitators who gained knowledge about the experiences of side-lined youth through their own experiences as a side-lined youth), in comparison to those with learned experiences (i.e., coaches who gained personal knowledge of the side-lined demographic through secondary methods such as reading and witnessing rather than facing the same lifestyle challenges). A logic model was used to illustrate the more empowering outcomes of the approaches of those with lived experience in comparison to the more socializing outcomes of those with learned experiences. The results highlight the value of coaches' life experience and the role it may play in sport program facilitation for side-lined youth, and reveals possible avenues for coach training interventions.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".