Exercise is Medicine® Canada on campus casebook: Investigating the development, composition and experiences of Exercise is Medicine® Canada on campus groups
Bibliographic record
Abstract
Exercise is Medicine® is a global health initiative that strives to bring physical activity (PA) research into practice by promoting PA as a chronic disease prevention and management strategy. The Exercise is Medicine® Canada on Campus (EIMC-OC) program was established in 2013 to foster inter-professional relationships between exercise and health care professional trainees, while providing opportunities for students to implement PA promotion initiatives in their campus communities. The EIMC national body was exploring strategies to facilitate the sharing of best practices and enhance communication amongst the 34 established EIMC-OC groups. Recently, casebooks have been gaining popularity as a knowledge translation (KT) tool. The purpose of the current project was to work in partnership with the EIMC-OC group members to compile information about the development, composition and experiences of the groups into a comprehensive casebook. Representatives from interested EIMC-OC groups completed a preliminary survey and participated in a semi-structured interview. Group profiles were created and verified by group representatives. The EIMC-OC KT Casebook includes detailed information about the structure, initiatives, barriers, facilitators, and lessons of 12 EIMC-OC groups from six provinces. The Casebook provides tangible examples of community-based efforts to promote PA within university and college communities. The Casebook will be disseminated to support the sustainability of EIMC-OC interventions by providing direction for current EIMC-OC groups and for students interested in implementing a new EIMC-OC group. In general, casebooks have the potential to serve as a KT tool for sharing ground level experiences and identifying potential program adaptations for multi-site programs.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".