Exploring the experience of using music and creative mark-making as a reflective tool during coaching supervision: An Interpretative Phenomenological Analysis
Bibliographic record
Abstract
Coaching supervision is still an emergent profession with a limited body of research to support its credibility and practice. This qualitative study is the first to explore the use of music and mark-making as a creative tool within coaching supervision and highlights information about both coach and coach supervisor experience. The research explores the question, ‘How does using mark-making in response to music within coaching supervision affect coaches’ experience of reflective practice?’ through semi-structured interviews, analysed using Interpretative Phenomenological Analysis (IPA) methodology. Findings revealed that using music and mark-making as a creative tool within coaching supervision enhances reflective practice and supports the client-supervisor relationship, enabling highly effective supervision to take place. The results offer coaches, coaching supervisors, coach educators and researchers and other professionals in other contexts where supervision forms an integral part of professional support and development insights into using music and other creative tools in supervision sessions and the impact on reflective practice. Keywords: coaching supervision, music, creativity, coaching psychology, reflective practice
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.017 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".