An Examination of the Relationship Between Coaches’ Transformational Leadership and Athletes’ Personal and Group Characteristics in Elite Youth Soccer
Bibliographic record
Abstract
There is a growing body of the literature highlighting the positive impact of transformational leadership behaviours across contexts, including sport. However, there is a lack of knowledge of this relationship within elite sport settings. Thus, the purpose of the present study was to examine the relationship between elite youth athletes’ perceptions of coaches’ transformational coaching-behaviours and variables that have been linked to transformational leadership in other settings (i.e., group cohesion, motivational climate, self-regulation of learning and athlete satisfaction). Norwegian elite youth soccer players (n= 753) selected into the national talent development program completed questionnaires to measure the variables of interest. Using structural equation modelling, results revealed a positive path from transformational leadership to both task and social cohesion, task-oriented motivational climates, self-regulation of learning and athlete satisfaction. Finally, a negative path from transformational leadership to ego-oriented climates was identified. The findings are in line with previous research in associating transformational leadership behaviours with adaptive outcomes, and further indicating that such relationships may also be valid in elite sport contexts.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".