Determinants of injury among older Saskatchewan farm operators: A prospective cohort study
Bibliographic record
Abstract
SIGNIFICANCE: The agricultural industry differs from other businesses in the composition of its workforce. Often farm owner-operators work beyond what society would expect to be a normal retirement age. Older farmers may be less receptive to behavioral changes designed to improve worksite safety and are at increased risk for experiencing a work-related injury. We had a unique opportunity to evaluate the relative influence of specific occupational conditions and practices reported by older farm operators (age ≥55 years) on the occurrence of injury using a longitudinal approach. MATERIALS AND METHODS: Baseline data were provided by eligible and consenting farm members in the first quarter of 2013. These farms were then followed longitudinally by mail surveys over 24 months to document injury experiences. For each survey, mailed questionnaires were sent to participating farms and completed by a single respondent. Cox proportional hazard models were used to determine which characteristics of the farm work environment were protective. RESULTS: A total of 96 farm injuries were reported by 73 of 566 farm operators. Medium (hazard ratio [HR] = 0.58; confidence interval [CI], 0.35-0.96) or high (HR = 0.53; CI, 0.30-0.94) worksite physical safety and high economic security (HR = 0.41; CI, 0.24-0.71) were protective in reducing injury among older farmers. CONCLUSION: Safety features in the physical environment and economic security are important protective factors for injury among older farmers. This supports injury prevention theory that suggests that engineering controls are superior to changes in work practices or the use of personal protective equipment in reducing injuries among older farmers.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".