“It Doesn’t Feel Like I’m Coaching”: Using a Kinesio-Cultural Exploration to Become a More Ethical Rhythmic Gymnastics Coach
Bibliographic record
Abstract
Rhythmic gymnastics (RG) is a sport that combines complex technical movements with hand-held apparatus, which, in turn, is used as an extension of the body’s movement. Therefore, coaching RG requires specialized knowledge for the athletes to successfully develop the required technical skills. In Canada, RG coach education is primarily delivered through formalized courses and informal learning of coach mentoring, experiential learning as a gymnast within a club setting, and copying examples from top international coaches. Traditionally, RG coaching has followed authoritarian coaching practices with the coach dictating the training to focus specifically on repetition of RG specific skills. These coaching practices can have unintended harmful, long-term consequences. In this study, I develop my own practice as an RG coach to consider more ethical coaching. To do this, I employ Action Research to implement a novel approach to skill learning, kinesio-cultural exploration (KCE), that requires me to reconceptualize skill development in a competitive RG setting and challenges the traditional authoritarian relationship between coach and gymnast.
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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 | 0.019 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.017 | 0.022 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.003 | 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".