Coach Education and Learning Sources for Coaches of Masters Swimmers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Masters Athletes (MAs; adult athletes typically over 35 years old who prepare in order to compete at levels ranging from very recreational competition to serious competition) want coaches to cater their approaches to working with adults. Using adult learning principles, we previously found that some coaches cater their approaches in ways to accommodate the manner in which adult athletes prefer to learn. The purpose of this article is to articulate swim coaches’ perceptions of how they learned to work with MAs and whether their formal coach training meets their needs related to coaching MAs. Eleven swim coaches were interviewed regarding how they learned to coach MAs, and were questioned specifically about their coach development broadly and coach education specifically. The data were thematically analyzed and results revealed six main learning sources: coaching experiences (e.g., interacting with MAs, reflection, advice from MAs, coaching youth), experience as an athlete, reading books and Internet searches, networks and mentors, formal coach education, and non-swimming experiences. Results also revealed key themes about coaches’ perceptions regarding coach education, specifically the lack of connection between coach education programs and the Masters sport context, and coaches’ interest in coach education specific to MAs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it