A Self-Reflective Toolkit of Adult-Oriented Coaching Practices in Masters Sport
Bibliographic record
Abstract
The Adult-Oriented Sport Coaching Survey (AOSCS) assesses psychosocial coaching practices for coaches who work with adult athletes. The AOSCS can be used as a self-assessment tool for coaches’ professional development, but there is a need to better understand its relevance for coaches. The purpose of this study was to explore coaches’ perspectives of the AOSCS as a self-assessment tool for reflecting, intuitively appraising, and provoking elaborations on contextually embedded psychosocial practices when coaching adult athletes. Thirteen Canadian coaches (nine women/four men, aged 59–78 years) completed the AOSCS prior to watching a webinar regarding the research on coaching Masters athletes and the development of the AOSCS. Each was subsequently shared a copy of their AOSCS results and interviewed about their perceptions of the relevance and utility of the AOSCS. Interviews were analyzed using reflexive thematic analysis, which resulted in three higher order themes (relevance of the AOSCS, using the AOSCS, and input from others) with six subthemes. The coaches see the AOSCS as provoking meaningful coach reflection, introspection, and learning intrapersonal coaching knowledge that serve ongoing coach development. As such, this paper outlines evidence with respect to the prospective relevance and practical utility of the AOSCS.
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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 | 0.016 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".