Intergenerational transfer of occupational risks on family farms
Bibliographic record
Abstract
BACKGROUND: Cultures of safety in farm work settings are under the authority of a responsible owner-operator, who establishes rules, attitudes, and behaviors for farm work practices. This novel analysis provides new evidence to show that risks that can lead to injury and are commonly practiced on Canadian farms are indeed transferred between generations. METHODS: Baseline data were provided by representatives from eligible and consenting farms (n = 589) in the province of Saskatchewan, Canada, during the first quarter of 2013. Mailed questionnaires were sent to participating farms and completed by a single respondent. Questionnaires included scaled assessments of hazards and safety practices by farm operators, and young workers on each farm. Descriptive and multiple regression analyses were used to examine relationships between farm owner-operator risks and safety practices and those reported for the young workers. FINDINGS: Graphical descriptive analyses showed that as farm owner-operator risks increased, so did those reported for children and young workers. Similarly, as farm owner-operator safe work practices increased, young worker hazards decreased, albeit more modestly. The young worker hazard scale increased by 0.20 (95% CI: 0.10-0.30) points, and decreased by 0.08 (95% CI: -0.016 to -0.000) points for each one-point increase in the owner-operator hazard and safe work practices scales, respectively. CONCLUSIONS: Occupational health and safety risks and protections experienced on farms appear to be transferred between generations. This suggests the need to target farm owner-operators, the responsible authority on the farm, as a focus of primary prevention strategies aimed at injury risks to children and young workers.
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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 | 0.000 | 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) | 0.000 | 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".