Knowledge Transfer: How do High Performance Coaches Access the Knowledge of Sport Scientists?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of this research was to answer three specific questions: I) How do coaches perceive sport science research? ii) What sources do coaches consult when looking for new ideas? and iii) What barriers do coaches encounter when trying to access new information? All of the high-performance coaches involved in Canadian Interuniversity Sport (CIS) were contacted to complete an on-line survey related to these questions. There were 205 coaches who completed at least part of the questionnaire. There was a strong consensus that the CIS coaches believe that sport science makes an important contribution to high-performance sport. Gaps exist between what coaches are looking for and the research that is being conducted, especially in the area of tactics and strategies. Coaches are most likely to consult other coaches, or attend coaching conferences to get new information. Sport scientists and their publications were ranked very low by the coaches as a likely source of sport science information. The barriers to the coaches' access to sport science are the time required to find and read scientific journals, and lack of direct access to a sport scientist. Strategies to remove the barriers could include rewarding sport scientists for successful transfer of their knowledge to practice through direct communication with coaches.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it