Perceived Risk of Pesticide Exposure Among School Workers in San Carlos, Costa Rica
Bibliographic record
Abstract
Background: There is increasing literature examining the effect of pesticides on people in proximity to pesticide use. However, limited information exists on how bystanders perceive the risk of pesticides to their health. This study aims to explore how school workers perceive the exposure to pesticides in a region where agriculture is the dominant economic driving force, and how these perceptions vary by sociodemographic subgroup. Methods: A total of 143 school workers from five districts in the San Carlos region of Costa Rica responded to the Technical Prevention Notes (NTP-578) perceived risk survey. The Mann-Whitney U test along with a Bonferroni control determined the statistical significance between subgroups. The four main sections for analysis of the results were prior knowledge on pesticide-related risks, perception of control over pesticide exposure, perception of current health risk and general knowledge of pesticide exposure. Results: Statistically significant differences in perceptions were seen by location, sex, age, level of education and position. Males and teachers exhibited higher levels of prior knowledge of hazards, whereas the older population, people without a university degree and administrators had higher perception of control over exposure to pesticides. Conclusion: School workers are knowledgeable on exposure to workplace pesticides and are aware of the severity of risk associated with pesticide exposure. In line with results from other studies, the older population and university educated people had higher perceived control over mitigating affects of pesticides. Our findings suggest that school workers could play a vital role in increasing knowledge dissemination pathways on pesticide-related harms. Further research could help in transforming school workers and bystanders into stakeholders and advocates for buffer zones.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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 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".