Mortality following unemployment in Canada, 1991–2001
Bibliographic record
Abstract
BACKGROUND: This study describes the association between unemployment and cause-specific mortality for a cohort of working-age Canadians. METHODS: We conducted a cohort study over an 11-year period among a broadly representative 15% sample of the non-institutionalized population of Canada aged 30-69 at cohort inception in 1991 (888,000 men and 711,600 women who were occupationally active). We used cox proportional hazard models, for six cause of death categories, two consecutive multi-year periods and four age groups, to estimate mortality hazard ratios comparing unemployed to employed men and women. RESULTS: For persons unemployed at cohort inception, the age-adjusted hazard ratio for all-cause mortality was 1.37 for men (95% confidence interval (CI): 1.32-1.41) and 1.27 for women (95% CI: 1.20-1.35). The age-adjusted hazard ratio for unemployed men and women was elevated for all six causes of death: malignant neoplasms, circulatory diseases, respiratory diseases, alcohol-related diseases, accidents and violence, and all other causes. For unemployed men and women, hazard ratios for all-cause mortality were equivalently elevated in 1991-1996 and 1997-2001. For both men and women, the mortality hazard ratio associated with unemployment attenuated with age. CONCLUSIONS: Consistent with results reported from other long-duration cohort studies, unemployed men and women in this cohort had an elevated risk of mortality for accidents and violence, as well as for chronic diseases. The persistence of elevated mortality risks over two consecutive multi-year periods suggests that exposure to unemployment in 1991 may have marked persons at risk of cumulative socioeconomic hardship.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".