Employment quality and mortality in Canada
Bibliographic record
Abstract
BACKGROUND: Research has shown that workers in non-standard (eg, temporary and part-time) employment experience poorer health outcomes than their permanent, full-time counterparts. However, previous studies have overlooked important differences in the quality of non-standard employment. To address this gap, we examined associations between a diverse typology of employment quality and mortality in Canada. METHODS: The 2006 Canadian Health and Environment Cohort (n=2 805 550) was linked to death records from 2006 to 2019. Employment quality was assessed according to an empirical typology describing five distinct employment arrangements: standard (secure and gainful), portfolio (demanding but gainful), marginal (limited hours and earnings), intermittent (sporadic and unstable) and precarious (insecure and low paying). Poisson regression models estimated covariate-adjusted associations between employment quality, all-cause and cause-specific (cancer, cardiovascular and unintentional injury) mortality, by sex/gender. RESULTS: We observed a graded association between employment quality and mortality. Mortality rates were lowest among workers in standard and portfolio employment. Mortality rates were highest among workers in precarious employment, with workers in marginal and intermittent employment occupying intermediate positions along the risk gradient. Associations varied by sex/gender, with larger absolute and relative mortality inequalities among men. CONCLUSIONS: Our findings reinforce the need to move away from a binary view of jobs as either 'standard' or 'precarious', encouraging a more nuanced understanding of contemporary employment arrangements and their health-related consequences. Policy interventions that promote access to high-quality jobs and protect workers exposed to precarious employment may yield substantial improvements in population health, including longevity.
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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 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".