Transformational Coaching Workshop: Applying a Person-Centred Approach to Coach Development Programs
Bibliographic record
Abstract
It is well established that coach learning and athlete outcomes can be enhanced through participation in Coach Development Programs (CDPs). Researchers advocate that the quality of CDPs can be improved by: (a) placing a greater emphasis on facilitating coaches’ interpersonal behaviours (Lefebvre, Evans, et al., 2016), (b) using appropriate and systematic evaluation frameworks to guide the evaluation of interpersonally-focused CDPs (Evans et al., 2015), and (c) incorporating behaviour change theories into the design and implementation of these CDPs (Allan et al., 2017). In doing so, the relevance of CDP content and the uptake of this content among coaching practitioners may be enhanced. Transformational leadership theory provides a valuable guiding framework for designing CDPs that aim to promote positive development in youth sport. Thus, the goal of the present paper is to outline the development of a novel, evidence-informed CDP: The Transformational Coaching Workshop and to provide practical strategies for the implementation of this workshop.
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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 | 0.029 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.006 | 0.016 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".