Examining How Elite S&C Coaches Develop Coaching Practice Using Reflection Stimulated by Video Vignettes
Bibliographic record
Abstract
The purpose of this study was to identify narrative types that illuminate how strength and conditioning (S&C) coaches used video vignettes in a guided reflection process to support the development of effective coaching practices. At the beginning of each week, over a 4-week period, 11 elite S&C coaches were sent a short video vignette clip of an S&C coach’s practice. They subsequently engaged in daily reflections in which they were guided to explore how the topic of the vignette aligned (or not) with their coaching practice. After the intervention, each S&C coach was interviewed regarding their process of learning from the vignette and from their reflections. Using a holistic narrative analysis of form and structure, the results exemplified three narrative types: performance, achievement, and helper. The S&C coaches whose reflections fitted the performance narrative type focused on their own practice, with limited consideration of the athletes’ perspective or the vignette. The S&C coaches whose reflections fitted the achievement narrative type strove to accomplish goals with their athletes and were selective in considering the vignette. The S&C coaches whose reflections fit the helper narrative type found that the vignette helped them consider an athlete-centered coaching approach focusing on the athletes’ well-being, as well as athletic abilities. Thus, S&C coach developers should utilize a guided reflection process that focuses on encouraging a coaching approach based on the helper narrative type.
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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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".