Re-Conceptualising Coach Education from the Perspectives of Pragmatism and Constructivism
Bibliographic record
Abstract
The aim of this paper is to offer a coherent philosophical position to underpin the task of the education of coaches. Our argument builds from an analysis of the specificity and issues concerning the development of coaches. We provide a potential explanation of these issues by identifying a significant discrepancy between two typical conceptualisations of coaching that in turn leads to differences in the principles of training, education and validation of coaching expertise. In contrast to a dominant modernist view, we argue for a conceptualisation that is based on the perspectives of pragmatism and constructivism that, in our view, better aligns with the fundamental attributes of professionalism as well as the way coaches see themselves. We describe how elements reflecting this position are operationalized in the educational programmes that we offer, together with a discussion of the consequences of applying these principles and implications for coaching stakeholders.
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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 | 0.022 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.060 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.010 |
| 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".