Shift work trends and risk of work injury among Canadian workers
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to examine the risk of work injury across shift work types in a -representative sample of Canadian workers. METHODS: We used the Survey of Labour and Income Dynamics to investigate trends in work injury by shift type between 1996-2006. Work injury was defined by receipt of workers' compensation. Logistic regression was used to estimate the risk between shift type and worker injury after adjusting for potential confounders. RESULTS: The rate of work injury decreased overall between 1996-2006, but did not decline for night shift -workers. Night shift work was associated with work injury for women [odds ratio (OR) 2.04, 95% confidence interval (95% CI) 1.13-3.69] and men (OR 1.91, 95% CI 1.21-3.03), while rotating shift work was associated with work injury for women (OR 2.29, 95% CI 1.37-3.82). The excess risk of work injury attributed to shift work was 14.4% for women and 8.2% for men based on population attributable fraction estimates. CONCLUSIONS: Rotating and night shift workers appear to have a higher risk of work injury, particularly among women. Regulatory agencies and employers need to identify and mitigate factors that give rise to increased work injury among these types of shift workers.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".