Assessment of Pesticide Exposure Control Practices Among Men and Women on Fruit-Growing Farms in British Columbia
Bibliographic record
Abstract
Exposure to pesticides can be reduced by wearing personal protective equipment (PPE) or by implementing alternative pest control techniques, such as Integrated Pest Management (IPM). A cross-sectional telephone survey was conducted to explore the prevalence of these practices and the factors that may be associated with them among men and women involved in fruit growing in British Columbia (BC), Canada. Survey variables were developed using a framework that incorporated aspects of farm structure, health promotion, and risk perception theories. Three hundred and eighty people took part in the survey (response rate 75%). Of those who applied pesticides (n = 119), 63% indicated that they usually wore PPE during application. Individual equipment use varied. Gloves were worn most frequently (84%), followed by a spray suit (77%) and breathing protection (75%). Peer-related factors and farm-specific characteristics such as the type of crops grown were most strongly associated with PPE use, whereas perception of pesticide risk was only weakly associated with this practice. IPM techniques had been tried on 62% of the conventional farms in the study. A range of factors was significantly associated with the use of IPM, including cultural, attitudinal, experiential, and risk-based and farm-specific variables. These results suggest that decisions to adopt exposure control practices may reflect consideration from the multiple dimensions that make up farm life, including structural characteristics of the farm as well as the attributes of the individuals who live on farms. These findings provide a better understanding of current practices and may help in the development of programs to promote pesticide exposure control practices in the BC farming community.
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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".