The implementation of an athlete leadership development program with youth ice hockey players
Bibliographic record
Abstract
Leadership in sport is considered a crucial factor for any team to achieve success. Researchers have found a positive relationship between athlete leadership and a variety of group dynamic outcomes. The present study focused on two of these outcomes: cohesion and collective efficacy. In particular, the purpose of the current study was to examine the effects of a season-long athlete leadership development program on perceptions of athlete leadership behaviours, cohesion, and collective efficacy. The participants were 14 elite youth hockey players (M = 16.46, SD = 0.78) from one competitive team. Players participated in six athlete leadership development workshops over the course of the season. Each workshop lasted approximately 45 to 60 minutes. Using a mixed-method approach, quantitative data were collected prior to the athlete leadership development program and following the program. Specifically, the players completed measures assessing athlete leadership behaviours (Leadership Scale for Sports, Chelladurai & Saleh, 1980; Differentiated Transformational Leadership Inventory, Callow et al., 2009), cohesion (Youth Sport Environment Questionnaire; Eys et al., 2009), and collective efficacy (Collective Efficacy Questionnaire for Sports, Short et al., 2005). In addition, in-depth qualitative interviews with the players were conducted following the athlete leadership development program. Taken together, the leadership development program was beneficial in fostering the players' leadership behaviours, and helped maintain their levels of cohesion and collective efficacy. Implications for developing leadership behaviours with the objective of enhancing cohesion and collective efficacy will be discussed
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".