A comparison of current and preferred government funding for the development of elite athletes in Canada
Bibliographic record
Abstract
In recent years, there has been considerable debate as to where Government funding should be prioritized in terms of an effective athlete development system. A major recurrent theme among many in the sporting community is the lack of funding at the lower end of the athlete development spectrum, particularly for club/grassroots programs. At the same time there is also a countrywide demand for additional funding to support elite athletes. -- The present study looks at how Government funding for sport in Canada should be allocated throughout the athlete development process. However, a major focus was placed on preferred funding for elite athletes. A survey was constructed to collect data on (a) respondents personal sport funding experience, and (b) their beliefs about which stages of the athlete development model funding should be prioritized to ensure the greatest benefit to athletes. The survey was distributed and responses were collected via the Internet . Participants included elite athletes and coaches as well as National Sport organizations.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".