Reducing Pesticide Exposure and Associated Neurotoxic Burden in an Ecuadorian Small Farm Population
Bibliographic record
Abstract
The contribution of community-based interventions, including farmer field schools (FFSs) in integrated pest management (IPM), to reducing pesticide exposures and associated neurotoxic burden among small-farm families in Ecuador was assessed in three Andean farming communities in a co-design of targeted action-research. Baseline questionnaire surveys elicited pesticide-related knowledge, practices, and exposure and neurobehavioral assessments were done using an adapted WHO battery. Pesticide applications on plots farmed by FFS versus non-FFS participants were compared. A year later, repeated surveys of participating households (n = 29) and neurobehavioral testing of individuals (n = 63) permitted comparisons of pre- and post-intervention values. The FFS graduates applied pesticides on their plots less frequently (p = 0.171). FFS households had increased pesticide-related knowledge of labels and exposure risk factors (both p < 0.004), better pesticide-handling practices (p < 0.01), and less skin exposure (p < 0.01). Neurobehavioural status had improved, particularly digit span and visuo-spatial function, resulting in overall z-score increases. Thus, community interventions reduced pesticide use, reported skin exposure, and neurotoxic burden among smallholder farm families.
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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 | 0.000 | 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 | 0.000 | 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 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".