University serial winning coaches’ experiences with low performance and maladaptive team culture
Bibliographic record
Abstract
We sought to explore the strategies and behaviours employed by University serial winning coaches during seasons of both low performance and a maladaptive team culture. We interviewed seven University team sport coaches and subsequently analyzed the data using a reflexive thematic analysis (RTA). Results indicated that our coaches generally felt unprepared for the unexpected and challenging season, leading to increased stress and decreased psychological well-being. Coaches experienced frustration, disappointment, and self-doubt, which was either exacerbated or mitigated by their access to social support. Despite the emotional turmoil coaches experienced, they were able to reflect on their actions and take away key lessons, helping them perform well in the future. Findings provide insight into how winning coaches manage and overcome inevitable adverse situations. Moreover, these results provide a deeper understanding of how these highly successful coaches navigate these key challenges that over time can inform policy and practice in coach development. These coaching strategies may help coaches of all levels overcome barriers to success and may be transferable to leaders of all levels across a range of disciplines outside of sport.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".