Evaluating Mental Health and Well-Being Services at a Canadian University
Bibliographic record
Abstract
In the last decade, a growing body of research has explored the importance of promoting mental health and well-being in university students. Being in university can be a stressful time for many, and as such, it is important to ensure students are experiencing high levels of mental health and well-being so that they can succeed in their studies. With the goal of maximizing mental health and well-being for university students, many universities offer wellness resources for their students. However, the accessibility and applicability of these wellness resources is not well understood. Research supports the notion that many students are unaware or unsatisfied with the mental health services, and/or may experience potential barriers to help-seeking at their college or university. As such, this study seeks to evaluate a Canadian University's wellness services and determine their impact on mental health and well-being. This study will explore whether wellness resources are meeting student expectations, and if there are any barriers to accessing them. Lastly, this study will consider whether mental health and well-being services offer additional benefits such as lowering stress and promoting resilience and positive emotions.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".