Effect of summer outdoor temperatures on work-related injuries in Quebec (Canada)
Bibliographic record
Abstract
OBJECTIVE: To quantify the associations between occupational injury compensations and exposure to summer outdoor temperatures in Quebec (Canada). METHODS: The relationship between 374,078 injuries compensated by the Workers' Compensation Board (WCB) (between May and September, 2003-2010) and maximum daily outdoor temperatures was modelled using generalised linear models with negative binomial distributions. Pooled effect sizes for all 16 health regions of Quebec were estimated with random-effect models for meta-analyses for all compensations and by sex, age group, mechanism of injury, industrial sector and occupations (manual vs other) within each sector. Time lags and cumulative effect of temperatures were also explored. RESULTS: The relationship between daily counts of compensations and maximum daily temperatures reached statistical significance for three health regions. The incidence rate ratio (IRR) of daily compensations per 1°C increase was 1.002 (95% CI 1.002 to 1.003) for all health regions combined. Statistically significant positive associations were observed for men, workers aged less than 45 years, various industrial sectors with both indoor and outdoor activities, and for slips/trips/falls, contact with object/equipment and exposure to harmful substances/environment. Manual occupations were not systematically at higher risk than non-manual and mixed ones. CONCLUSIONS: This study is the first to quantify the association between work-related injury compensations and exposure to summer temperatures according to physical demands of the occupation and this warrants further investigations. In the context of global warming, results can be used to estimate future impacts of summer outdoor temperatures on workers, as well as to plan preventive interventions.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".