Work and mental health: The experience of the Quebec workforce between 1987 and 1998
Bibliographic record
Abstract
This study examines the distribution of psychological distress in twelve occupational groups over the decade 1987-1998 in the Quebec workforce. Cross-sectional data from the three phases of the Quebec Health and Social Survey are used with n = 9,450 in 1987, n = 10,947 in 1992 and n = 10,960 in 1998, totalling 31,357 workers aged 15 and over. Occupations are classified according to the Canadian Socio-economic Classification of Occupations. Prevalence estimates for occupational groups are computed and logistic regression analyses are conducted controlling for gender, age and marital status. The results show that the prevalence of workers with psychological distress increased sharply between 1987 and 1992 and declined back in 1998 but still increased compared to 1987. However, only non-qualified white collars, semi-qualified blue collars and male non-qualified blue collars show a significant increment in psychological distress over time. Analysis of the differentials in the prevalence of psychological distress gives greater odds of distress for supervisors, semi-qualified white and blue collar workers compared to upper managers. The odds for occupations are stable over time, gender, age and marital status. The odds of female workers significantly decreased in the three phases. It appears that the restructuring of the work environment and the perturbations in the larger society promoted an increase of psychological distress within definite segments of the workforce. The specific contribution of occupation is limited but supervisors and occupations requiring lower qualifications are more at risk regarding mental health at work.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".