Socioeconomic Status and Injury in a Cohort of Saskatchewan Farmers
Bibliographic record
Abstract
PURPOSE: To estimate the strength of relationships between socioeconomic status and injury in a large Canadian farm population. METHODS: We conducted a prospective cohort study of 4,769 people from 2,043 farms in Saskatchewan, Canada. Participants reported socioeconomic exposures in 2007 and were followed for the occurrence of injury through 2009 (27 months). The relative hazards of time to first injury according to baseline socioeconomic status were estimated via Cox proportional hazards models. FINDINGS: Risks for injury were not consistent with inverse socioeconomic gradients (adjusted HR 1.07; 95% CI: 0.76 to 1.51 for high vs low economic worry; adjusted HR 1.72; 95% CI: 1.23 to 2.42 for completed university education vs less than high school). Strong increases in the relative hazard for time to first injury were identified for longer work hours on the farm. CONCLUSIONS: Socioeconomic factors have been cited as important risk factors for injury on farms. However, our findings suggest that interventions aimed at the prevention of farm injury are better focused on operational factors that increase risk, rather than economic factors per se.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".