Walking the Talk: Toward Creating Mentally Healthy Business Schools
Bibliographic record
Abstract
Institutions of post-secondary management education are facing increased pressure to address the mental health challenges of their student population. Yet, many institutional members are unsure or unaware of measures they can engage in to improve mental health outcomes for students. In this paper, we build on the work of the Okanagan Charter: An International Charter for Health Promoting University and Colleges as well as Canada’s National Standard for Mental Health and Well-Being for Post-Secondary Students to provide concrete actions for business school stakeholders (e.g., administration, faculty, staff, and students), to craft policies, develop programs, and offer individualized services that meet the emerging needs of students. By viewing mental health as a shared responsibility and working together to improve student outcomes and embedding mental health and wellness into core institutional activities, business schools have the opportunity to strengthen their mandate of contributing to business and society.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.018 | 0.008 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".