Bibliographic record
Abstract
Coaching science is a thriving sport science with a history of overlapping topical, methodological, and conceptual shifts drawing from humanist and poststructural lenses. Recently, a deeper engagement with the possibilities of inquiring through a posthumanist lens has been proposed, opening ontological passageways for coaching scholars to think and do coaching science differently. In efforts to expand upon recent posthumanist experiments in coaching science, the purpose of the present paper lies in situating sport coaching as intra-action using Barad’s (2007) agential realist ontology and diffractive methodology. Ontological shifts from learning to becoming and reflection to diffraction are proposed, setting the stage for moving inquiry in coaching science from the coach to coaching intra-action. By situating sport coaching in agential realist rhythms, coaching scholars can promote creativity, expand horizons for what coaching science can do, and multiply who/what is included in coaching intra-action.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.034 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".