Thoughts on being the gadfly in the sport sciences ointment: building the road to meta-theoretical research creation
Bibliographic record
Abstract
In this paper, the quality, position and relevance of social science research in sport science will be reviewed from a philosophical perspective. Using metaphors, such as the Socratic ‘Gadfly’, it will be argued that one of the major challenges the social science researcher faces is the paradigmatic differences in sport science and the dominance of the natural/biological science paradigm in most cases. It will be further proposed that to attempt to address that challenge and engage in new research creation, we require a critical perspective that explores meta-theoretical foundational analysis. This exploration will include examples of non-formal reasoning as a potential method of bridging the gap between the paradigms and building meta-theory of sport science. Such a union presents a challenge precisely because these paradigms differ in their methods, assumptions of what constitutes legitimate research and, perhaps most fundamentally, their assumptions regarding the very relationship of human beings to sport.
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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 | 0.084 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.010 | 0.127 |
| Scholarly communication | 0.022 | 0.050 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.008 | 0.015 |
| Insufficient payload (model declined to judge) | 0.005 | 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".