Creating Value in a Sport Coach Community of Practice: A Collaborative Inquiry
Bibliographic record
Abstract
Coach education researchers have suggested that coaches require ongoing support for their continued learning and development after initial certification. Communities of practice have been used in a variety of settings, and have been identified as an effective means for supporting coach learning and development. However, researchers have yet to fully explore the value that can be created through participating in them within sport settings. The purpose of this study was to collaboratively design, implement, and assess the value created within a coach community of practice, using Wenger, Trayner, and De Laat’s (2011) Value Creation Framework. Participants included five youth sport coaches from a soccer organization. Data collection included observations and reflections from the first author throughout the study, two individual interviews with each coach, and interactions via an online discussion platform. The findings revealed that the coaches created value within each of the five cycles of value creation in Wenger and colleagues’ framework, and that they created value that was personally relevant to their immediate coaching needs. The coaches’ learning led to an increase in perceived coaching abilities.
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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 | 0.041 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.014 | 0.020 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".