P-108 Population-level estimates of occupational exposure to chlorothalonil, 2,4-D, and glyphosate in Canada’s agricultural industry (CAREX Canada)
Bibliographic record
Abstract
<h3>Introduction</h3> Certain pesticides may lead to adverse health outcomes including cancer; however, little is known about occupational pesticide exposure in Canada. <h3>Objective</h3> The purpose of this study was to estimate the prevalence and likelihood of occupational exposure to chlorothalonil, 2,4-D, and glyphosate in Canada’s agricultural industry. <h3>Methods</h3> Lower and upper estimates were calculated using the Canadian Census of Population (CoP) and Census of Agriculture (CoA). We estimated the number of workers and proportion of farms applying ‘herbicides’ or ‘fungicides’ by farm type using CoA survey data. These values were multiplied to yield the number of workers at risk of exposure. Likelihood of exposure (exposed, probably exposed, possibly exposed) was qualitatively assigned using information on crop type, primary expected tasks, crop production practices, and residue transfer data. Agricultural workers who are at risk of exposure but were not captured by the CoA were identified using the CoP. <h3>Results</h3> An estimated 37,700 to 55,800 workers (11–13% of agricultural workers) were exposed to glyphosate in in Canada while 30,800 to 43,600 workers (9–11%) and 9,000 to 14,100 (3%) were exposed to 2,4-D and chlorothalonil, respectively. Approximately 70–75% of at-risk workers were probably or possibly exposed to any of the pesticides. Glyphosate exposure was most common among workers in oilseed (29%) and dry pea/bean farms (28%), along with those providing support activities for farms (31%). 2,4-D exposure was most common in corn (28%), other grain (28%), and soybean farms (27%), while chlorothalonil exposure was more likely among greenhouse, nursery and floriculture workers (42%) and those working on farms (28%, for occupations not captured by the CEAG). Regional variations reflected differences in farm types by province. <h3>Conclusion</h3> This study estimated the prevalence of occupational pesticide exposure in Canada, and findings can support priority setting for future research and data collection.
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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) | 0.001 | 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".