Do occupation and work conditions really matter? A longitudinal analysis of psychological distress experiences among Canadian workers
Bibliographic record
Abstract
This study analyses the relationship between occupation, work conditions and the experience of psychological distress within a model encompassing the stress promoted by constraints-resources embedded in macrosocial structures (occupational structure), structures of daily life (workplace, family, social networks outside the workplace) and agent personality (demography, physical health, psychological traits, life habits, stressful childhood events). Longitudinal data were derived from Statistics Canada's National Population Health Survey and comprised 6,359 workers nested in 471 occupations, followed four times between 1994-1995 and 2000-2001. Discrete time survival multilevel regressions were conducted on first and repeated episodes of psychological distress. Results showed that 42.9 per cent of workers had reported one episode of psychological distress and 18.7 per cent had done so more than once. Data supported the model and challenged the results of previous studies. The individual's position in the occupational structure plays a limited role when the structures of daily life and agent personality are accounted for. In the workplace, job insecurity and social support are important determinants, but greater decision authority increases the risk of psychological distress. Workplace constraints-resources are not moderated either by the other structures of daily life or by agent personality.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".