Profiling Coach Openness to Positive Youth Development Before, During, and After Their Participation in a Coach Education Course
Bibliographic record
Abstract
Given that coaches who enroll in coach education courses may have diverse levels of openness to learning about positive youth development (PYD), the purpose of this study was to profile coaches’ openness to PYD before, during, and after their participation in a coach education course. A multimethod approach that involved field notes, nonparticipant observations, and interviews was used to create three profiles illustrating coaches’ varying levels of openness. Participants were three male coaches involved in competitive and recreational youth sport who had been coaching youth for more than 12 years. The profile of Graham represents a coach who was open to PYD. The profile of Fonseca represents a coach who was partially open to PYD. Finally, the profile of Taylor represents a coach who had no openness to PYD. Results are discussed in relation to how performance outcomes remain a high priority in youth sport, compelling some coaches to pay “socially desirable lip service” to PYD without any real intentions to modify their coaching practice. Revised policies and funding models, developed with input from multiple levels of stakeholders in the sport system, may prove useful in inspiring more coach openness to learning about PYD. This study may help further our understanding on how coach educators can use differentiated pedagogical approaches that may help make PYD a worthwhile and tangible objective for coaches who register in PYD coach education courses. Moving forward, future investigations on coach openness could be expanded to other sport contexts and coach development systems.
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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 | 0.004 | 0.011 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.004 |
| 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".