Enhancing Support for Student Mental Health and Wellbeing through Service Renewal at a Canadian College
Bibliographic record
Abstract
As the postsecondary education sector has evolved toward mass education, the proportion of students studying at postsecondary institutions experiencing mental health and wellness-related challenges has continued to rise. This continued growth in prevalence and severity of mental health and wellness conditions impacting students in the postsecondary sector has occurred without similar growth in resourcing for departments responsible for supporting these students in successfully navigating their learning environments. These realities require that institutions begin developing strategies to address this gap. This Organizational Improvement Plan (OIP) presents a possible solution to enhance the capacity of a large urban College in Canada to support the increasing complexity of, and demand for, mental health and wellness-related services and interventions which foster students’ personal and academic success.\nIntroducing the Model for People-Centred Leadership through Praxis (PCLP Model), which incorporates principles of transformational and distributed leadership through a social justice lens, this OIP addresses the gap between institutional capacity and student demand for support while also navigating the process of amalgamating personal counselling and accessible learning departments. Through meaningful engagement and co-construction, this OIP focuses on three key priorities: unifying the team’s vision and values, identifying opportunities to enhance services and collaborative approaches, and communicating and integrating the new state into the institutional culture. This OIP may provide a model for other institutions working toward empowering students in meeting their wellness goals while creating conditions that maximize students’ potential to thrive.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.003 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.003 | 0.008 |
| 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".