Translating a self-reflective instrument into practice: Coaches use of the adult-oriented sport coaching survey in a masters coach development intervention
Bibliographic record
Abstract
Masters sport clubs/leagues are for adults who practice and compete in sport that is promoted to people who are beyond the normative age of peak performance in their respective sports (Callary et al., 2021). Belalcazar and Callary (under review) created and implemented a series of professional development workshops for coaches in a Colombian Masters football (soccer) league for men 60 years+ to develop adult-oriented coaching practices. Thus, central in this investigation was the use of the Adult-Oriented Sport Coaching Survey (AOSCS; Rathwell et al., 2020). The purpose of this presentation is to (a) explore specific AOSCS items and themes that the Colombian Masters football league coaches chose to work on through the workshops to further develop face validity of the items and themes, and (b) to demonstrate translational validity of the items and themes into a functioning and operating reality. Data from 17 coaches who participated in the workshops were collected from their AOSCS results, discussions, and micro-facilitations during the workshops. A content analysis revealed that coaches focused mainly on Framing Learning Situations, Considering the Individuality of Athletes, and Creating Personalized Programming. When working in groups, they also focused on Creating Personalized Programming, and Framing Learning Situations wherein they could use the AOSCS items in practice and games. Determining the coaches' specific interests in using the AOSCS furthers our understanding of the workshops as a collaborative learning environment that supports coach development, and confirms that the AOSCS can be used as a self-reflective instrument for Masters coach development interventions.Acknowledgments: This project was supported by funding from the Social Sciences and Humanities Research Council Canada Graduate Scholarship
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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 | 0.037 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".