Athlete leadership development in youth hockey players
Bibliographic record
Abstract
Athlete leadership has been found to be critical for achieving effective team functioning and performance (Bucci et al., 2012; Gould et al., 2002). Further, researchers have highlighted the importance of including all team members in leadership development training since all athletes can provide leadership to their team (Crozier et al., 2013). However, theoretically and empirically tested athlete leadership development programs are not common in the literature. Using Duguay et al.'s (2017) athlete leadership development program, the purpose of the present study was to implement an athlete leadership development program targeting the enhancement of leadership behaviours for youth hockey players. Participants were 15 male Peewee Minor hockey players from one competitive team. The leadership development program consisted of six, one-hour long sessions that occurred twice monthly. Each session comprised an introduction to the leadership behaviours, small group and/or independent activities, and a debrief led by the coaching staff. The data were derived from continuous observations of the players, and a diary based on observations from the principal researcher during the hockey season that included perspectives from both the players and coaches. An improvement in communication and social cohesion amongst the players was found over the course of the intervention. Further, the leadership development program was beneficial for the coaches by allowing them to practice and reflect on the same leadership behaviours as those addressed to the players (Nelson et al., 2006).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".