Planning for the development of strength and conditioning coaches’ psychosocial competencies
Bibliographic record
Abstract
Co-produced research can engage academics with non-academic partners to improve policy and practices in everyday life. Accordingly, we collaborated with the United Kingdom’s Strength and Conditioning Association (UKSCA) stakeholders. As an ongoing participatory action research (PAR), in phase one we explored the lack of psychosocial competencies in the UKSCA’s predominantly positivist and bioscientific coach education curriculum and their suggestions for change. This manuscript focuses on the planning step of phase two of our PAR. Twenty-six UKSCA stakeholders engaged in focus groups or one-on-one interviews where they discussed their knowledge, beliefs, feelings, and suggestions of learning psychosocial coaching competencies as part of the UKSCA’s coach education and accreditation pathway. We used a thematic narrative analysis to create one story involving five sequential themes that build towards a plan for the UKSCA’s curriculum changes. The narrative arc starts with the stakeholders uncovering the central problem – the lack of psychosocial competencies. Then, the stakeholders identify the current curriculum as scientific and objective, explore how psychosocial competencies are currently learned through experience, and the story climaxes with a debate on the need for change. In the resolution, they suggest actions for change, particularly a new module for the UKSCA, taught by psychosocial content experts. In the challenge of introducing new disciplinary knowledge to the field of strength and conditioning, the story outlines how PAR can lead to the organisation of a practical plan for ongoing co-production, which may shape coaches’ knowledge construction and a plurality of ontological and epistemological perspectives within the UKSCA.
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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 | 0.047 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".