A Sport Leader's Attempt to Foster a Coaches' Community of Practice
Bibliographic record
Abstract
This case study examines a sport leader's attempt to foster a coaches' community of practice in a competitive youth baseball league. It is analysed using Wenger's [8] community of practice framework. Interviews were conducted with seven participants including the sport leader (technical director), the league manager, and five coaches. The retrospective account of time period 1 (covering four years) portrays how a visionary leader instigated changes in the sport culture to have coaches share knowledge with the common goal of developing all of the league athletes. For example, the coaches were selected for their specific expertise and were given the responsibility for the corresponding players not only on their own team but on all teams in the league. Establishing a co-operative environment in a competitive context required strong leadership and presented challenges including the alignment of all the coaches, parents, and referees. The time period 2 (covering three years), also studied retrospectively, demonstrates that the loss of the visionary leader led to the return to a more traditional, competitive environment. Finally, the time period 3 (covering one year), which was the timeframe when the research project was conducted, shows a willingness to return to the collaborative ways of time period 1, but also the challenges in making this happen without the presence of a strong, visionary leader.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".