A Multi-Year Study of First-Year Engineering Student Well-being at a Large Canadian University
Bibliographic record
Abstract
A five-year study into student well-being at a large Canadian university is presented. Through weekly surveys tracking student well-being with the Short Warwick Edinburgh Mental Wellbeing Scale (WEBMWS), a gradual but persistent drop in student well-being over the academic year is consistently observed. Average well-being on WEBMWS over the five years corresponds to students feeling optimistic, useful, relaxed, etc. “some of the time,” and is consistent from year to year. Student rankings of key stressors each week reveal academics (high grades, workload, competitive program entry, and passing) dominate concerns, while stressors related to transitioning to first-year university are an order of magnitude less prevalent. Clear and statistically significant differences are noted between different student groups, with men tending to report better well-being than both women and non-binary students, with international students reporting slightly better well-being than Canadian students, and students with a mental disability reporting lower well-being than those without.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".