Bibliographic record
Abstract
The prevalence of post-secondary student mental health concerns has led Canadian post-secondary educational institutions to identify student mental health as an ongoing issue and a burgeoning crisis, which demands immediate systemic, institution-wide action. Instructors are uniquely situated to promote student mental health, yet there is an insufficient understanding of how instructors can effectively engage in student mental health promotion and what institutional support instructors need. My research explores the ways that instructors currently engage in student mental health promotion and how the organization of a post-secondary institution supports or hinders efforts to do this work. Using a variety of qualitative research methods, I conducted an institutional ethnography of a large faculty at McGill University, exploring the way that institutional practices and policies regulate and shape the experiences of all members of the university community - students, administrators, staff members and instructors – vis-à-vis student mental health promotion. Focussing primarily on in-depth, semi-structured interviews with fourteen members of the university community, this study documents institutional support mechanisms (i.e., resources, supports, training, institutional organization) that facilitates instructor engagement in mental health promoting activities. The study reveals two primary types of mental health supporting activities: student supporting activities and assessment-related activities, illuminating how these activities are shaped by particular institutional policies, processes, and priorities, such as the University Student Assessment Policy and the tenure and promotions processes. The thesis culminates in recommendations for McGill University and more broadly, post-secondary institutions that wish to empower their instructors to engage in effective mental health promotion
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".