“Walking the Tightrope”: Reflections on Mobilizing Foucauldian Theory Within an Endurance Running Coach Development Intravention
Bibliographic record
Abstract
This paper presents our efforts and subsequent reflections in attempting to make Foucauldian theory accessible and relevant to a group of high-performance endurance-running coaches within the context of a coach development intravention and Foucauldian inspired workshop series. Specifically, we reflect upon our efforts to introduce coaches to Foucauldian ideas and concepts such as the knowledge–power–practice triad and upon the tensions we experienced in doing so. These tensions were related to the power of the theory–practice divide to set expectations around what it means to be an effective coach developer and a high-performance coach but also in the main related to our intentions regarding a broader shift in the coaches’ thinking concerning the influence of a number of social forces in the formation of their practices. We contend that coaching scholars invested in mobilizing ways of knowing underpinned by a different logic (e.g., relationally informed ways of knowing) within coaching and coach development settings would benefit from a deeper understanding of the politics of sports coaching knowledge and practice and how relations of power–knowledge impact learning within pedagogical contexts. Such an awareness, we believe, would in turn support more targeted pedagogical frameworks, practices, and strategies specifically aimed at disrupting established relations of power–knowledge and related problematic binary understandings such as the theory–practice divide which stand in the way of more diverse and ethical knowledge production processes in sports coaching and coach development work.
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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 | 0.053 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.032 | 0.084 |
| Scholarly communication | 0.019 | 0.017 |
| Open science | 0.005 | 0.028 |
| Research integrity | 0.010 | 0.028 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".