Using Knowledge Mobilization to Promote Student Engagement in Health Promotion on Canadian Campuses
Bibliographic record
Abstract
With the increased incidence of poor mental health in young adults, health promotion strategies are needed on campuses. World Cafés were held to facilitate discussion around three main topics: thoughts about findings emerging from a recent health survey; resources currently available on campus; and strategies or resources needed to improve student well-being. Participants readily provided insight into mental health concerns among students, and their recommendations focused primarily on creating a culture of well-being in the university, with more professional support services and greater health promotion. Overall, the World Café approach provided an effective method to engage students and discuss possible strategies to promote better mental health on campus. Étant donné l’augmentation des problèmes de santé mentale chez les jeunes adultes, il faut adopter des stratégies de promotion de la santé à l’université. Des conversations de type Café du monde – World Café – ont eu lieu autour de trois sujets : 1) des réflexions autour des résultats provenant d’un sondage récent pourtant sur la santé; 2) les ressources qui sont actuellement offertes à l’université; 3) les stratégies et les ressources nécessaires à l’amélioration du bien-être des étudiants. Les participants n’ont pas hésité à témoigner des enjeux de santé mentale dans la communauté étudiante. Leurs recommandations ont convergé principalement vers la création d’une culture du bien-être à l’université, ce qui suppose un accroissement des services d’aide professionnelle et de la promotion de la santé. Dans l’ensemble, la méthode de type Café du monde a permis de faire participer les étudiants et de discuter des stratégies potentielles pour la promotion de la santé mentale à l’université.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".