What Do We Know About Research on Parasport Coaches? A Scoping Review
Bibliographic record
Abstract
The purpose of this scoping review was to provide a broad overview of the literature pertaining to parasport coaches, including information regarding the size and scope of research, the populations and perspectives obtained, and the type of methods used to conduct the research. Data were collected and analyzed using a six-stage framework for conducting scoping reviews. The results revealed that the majority of articles were based on interviews, and an overwhelming majority of the participants were men coaching at the high-performance level in North America. Three of the most frequent topics were becoming a parasport coach, being a parasport coach, and having general parasport coaching knowledge. Articles ranged in date from 1991 to 2018, with 70% of empirical articles published from 2014 onward, indicating an emerging interest in this field of research. This review has the potential to advance the science and practice of parasport coaching at all levels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".