A Case Study of Using an Adult-Oriented Coaching Survey and Debrief Session to Facilitate Coaches’ Learning in Masters Sport
Bibliographic record
Abstract
The Adult-Oriented Sport Coaching Survey (AOSCS) can be used by coaches to reflect on how they coach competitive adult sports participants. There are coach (AOSCS-C) and athlete (AOSCS-A) versions. The purpose of this case study is to portray how coaches reflect on scores from the AOSCS with a coach developer. Nine coaches (White; ages 23–72; five men and four women; six sports) and their respective athletes were invited to complete the AOSCS twice during a season. Coaches were given their survey scores and undertook a debriefing interview with a coach developer. We reflected on four key topics in this dedicated professional development session: coach impressions on receiving an AOSCS personal scorecard, leveraging comparisons between coach and athlete scores, leveraging comparisons in scores over time, and misunderstandings/inadequacies of numerical scores. We reflect on meaningful interventions for coach development in adult 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 | 0.018 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".