The Hierarchy of Control in the Epidemic of Farm Injury
Why this work is in the frame
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Bibliographic record
Abstract
The application of the hierarchy of control (HOC) is a well-established approach to hazard reduction in industrial workplaces. However, it has not been generally applied in farm workplaces. The objective was to determine current practices of farmers in the context of a modified HOC, and the effect of these practices on farm injury outcomes. A self-reported mail survey of 1196 Saskatchewan farm operations was conducted in 2013. Selected survey questions were used as proxy measures of the farm owner-operator's practices relevant to each of the six steps of increasing importance in a modified HOC: (1) hazard identification; (2) risk assessment; (3) personal protection; (4) administrative controls; (5) engineering controls; and (6) elimination of the hazard. Analysis used basic descriptive statistics and logistic regression to examine associations of interest. When four of the six HOC steps were adhered to, there was a significant protective effect: odds ratio (OR) = 0.32 (95% confidence interval [CI]: 0.14-0.74) for any injury and OR = 0.27 (95% CI: 0.07-0.99) for serious injury in the overall study population. For farm owner-operators utilizing four of the six steps in the modified HOC, there was a significant protective effect for any injury (OR = 0.30, 95% CI: 0.11-0.83). Although there is a considerable absence of use of elements of the HOC among farm operators, for farmers who adhere to these steps, there is a significant reduction in their risk for injury. Prevention strategies that embrace the practice of these principles may be effective in the control of farm workplace injury.
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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 | 0.002 | 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) | 0.000 | 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 it