Extent and sources of occupational stress in university staff
Bibliographic record
Abstract
Canadian higher education sector has undergone numerous changes during the past decades. Increased student enrolments, massive cuts in human resources and constant restructuring are changes likely to have had a considerable impact on all employees (e.g., administrative, trades, and faculty). While many studies conducted in different countries have shown that stress in universities is a problem of alarming proportions, to date, no study of the entire staff of a university has been carried out in Canada. This research uses an approach based on the prevention and management of the sources of occupational stress to study 1086 employees of a Quebec university. Data were collected by means of questionnaires and semi-structured interviews. It was found that the proportion of individuals who reported a high level of psychological distress was twice as high (40%) than that reported for a Quebec-wide sample (20%). Work overload, the relationship with one's superior and participation in decision making were systematically reported as high risks to employees' health. It was found that human resources management practices have not followed the rapid organizational changes which affected the university in the past years. The results are discussed in light of the risk management approach.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".