Lifelong learning pathway of a coach developer operating in a national sport federation
Bibliographic record
Abstract
Coach developers play essential roles in “coaching the coaches,” and investigating their lifelong learning pathway is key for better understanding the mechanisms that lead certain coaches to become coach developers. Thus, the purpose of the paper was to conduct a case study to investigate the lifelong learning pathway of a coach developer operating in a national sport federation. The case investigated is Mille, a certified coach developer in charge of the Brazilian Rugby Federation’s coach education program. Data were collected through the Rappaport Time Line and two semi-structured interviews. An interpretative phenomenological analysis was adopted to explore the lived experiences reported by the participant. The results highlighted that Mille is an individual driven by challenges provided either by external factors (i.e. school, university, work) or by his own choices (i.e. becoming a coach, becoming a coach developer, starting a PhD) for personal and professional development. Specific life events led him to make decisions for evolving in his roles, from athlete, to coach, to coach developer, and to “master trainer,” which is the highest level of certification provided by World Rugby. Practical implications are suggested to contribute to the organization of education initiatives for coach developers through a lifelong learning perspective.
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How this classification was reachedexpand
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 | 0.003 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".