Work In-Progress: Mental Health Initiatives and TAO at the University of Windsor
Bibliographic record
Abstract
This paper documents a work in progress at the University of Windsor to expose our first-year students to mental health supports available on campus. The University of Windsor prides itself on being a leader in providing wellness and mental health services to its students as part of the institution’s comprehensive, multi-year Mental Health Strategy (http://www.uwindsor.ca/studentexperience/322/mental-health-strategy). As well, within the Faculty of Engineering, many new initiatives have been implemented to provide mental health services to our students, especially first-year students who are transitioning to university and, for some, to Canada. One such initiative is Therapy Assistance Online (TAO). TAO is an online library of interactive modules that helps students learn skills to handle challenges in their lives (http://www.uwindsor.ca/engineering/831/tao). TAO is available to all University of Windsor students; however, not all students use the service. In order to encourage Engineering students to use it, first-year students are introduced to TAO in their second-semester Technical Communications course. A course assignment asks students to complete four of the five modules within the Communication and Interpersonal Relationships TAO pathway. The five modules are: Managing Anger, Communication Strategies, Communication Styles, Problem Solving, and Relationships (this fifth module is available to students, but they are not required to complete it). At the time of writing, this initiative had only been completed over the course of one academic year; the second academic year was in progress. This paper will discuss how the initiative was implemented, changes that were made as it was developed, and instructor recommendations for further development. It is anticipated that additional undergraduate engineering courses will incorporate TAO pathways into their course requirements. Specific pathways include “Calming Your Worry” and “Let Go and Be Well”, which address topics like anxiety and resilience, respectively. As well, this paper will discuss additional wellness and mental health initiatives that are being implemented to support our first-year Engineering students such as mental health counselling, drop-in counselling, weekly therapy dog drop-in sessions, international student support services, and the creation of a new space within the Faculty of Engineering: the Engineering Student Support Services Centre in conjunction with the services currently offered at the WINONE office (First Year Engineering Office), making a home for incoming local and international students alike.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.009 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 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".