TITTLE DEVELOPING MODLES OF RESIDENTIAL AND PARAOCCUPATIONAL EXPOSURE TO PESTICIDES FOR AGRICULTURAL FAMILIES
Bibliographic record
Abstract
Background and Aims: CAREX Canada is a national occupational and environmental surveillance project estimating the number of Canadian exposed to carcinogens. Agricultural pesticide estimates are being developing to calculate cancer risks across the country. To facilitate these risk assessments, we examined the state of the literature on residential and para-occupational exposure and its implications for pesticide risk assessment. Methods: A search was undertaken in the published literature for data on exposures in farm homes as well for spouses and children of farmers and farmworkers, including exposure assessments and epidemiologic studies. Papers were limited to research from North America. Environmental and biological sampling and epidemiological data from these studies (n=42) were critically examined and catalogued in a matrix. Results: Para-occupational and residential pesticide exposures are clearly documented in North America. The studies showed increased exposures for farm children compared to non-farm children. A smaller increase was seen in some studies of farm spouses. Major sources of exposure included workers’ boots, clothes and vehicles. Children who were present during spraying showed even higher levels of exposure. Proximity of the home to spraying locations explained some, but not all, of the home exposure reported. Epidemiologic studies showed higher rates and risks of cancer and decreased neurobehavioral performance in children whose parents had occupational exposure to pesticides. We propose the need for a stratified farm community risk assessment model, with low (farm spouse), medium (children not present for spraying) and high (children present for spraying) exposure categories. Conclusions: (Arial, 8pt, bold) text (Arial, 8pt) dummy text, dummy text, dummy text, text, dummy text, dummy text, dummy text, dummy text, text, dummy text, dummy text, text, dummy text, dummy text, text, dummy text, dummy text, text, dummy text, dummy text, text, dummy text, dummy text, text, dummy text, dummy text, text, dummy text, dummy text, text.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".