Mental health and performance support in Canadian varsity sport: Current trends and promising practices
Bibliographic record
Abstract
University varsity athletes face multiple role demands in their efforts to balance school, life, and sport – a potentially stressful mix. To varying degrees, universities provide student-athletes with resources to prevent, protect, and handle the negative mental consequences that may be associated with student-athlete stressors. However, our understanding of the nature of resources and the extent to which they are making a difference is limited. To provide an overall picture, this research investigated mental health (MH) and performance (MP) resources offered to varsity athletes across Canada, comparing what is offered at various institutions. This subject was investigated by conducting semi-structured interviews with key informants from universities with established varsity athletic programs across Canada. Themes around resourcing and supports relate to navigation, accessing services, capacity building, and practical usage. Concerning barriers to MH and MP supports, financial, motivational, and communicational themes were identified. We offer suggestions to raise the quality of MH and MP resources offered to this population, including a community of practice among varsity support programs to innovate, develop, and share resources.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".