Pesticide safety practice and its determinants among small scale vegetables farmers in Eyasi area, Arusha region Tanzania
Bibliographic record
Abstract
Background: Strategies to achieve the millennium agricultural development goals include increased use of pesticides to increase agricultural production in poor countries. However, the increased availability and use of such chemicals need to be paralleled with national and personal level practices to maximize safety for communities and environment. Aim and methods: The aim of this study was to determine the pesticide safety practices among rural farmers in Karatu District in Northern Tanzania. Farmers practicing horticulture farming in Mang’ola Division were interviewed about their practices during and after pesticides application. Results: The study included 148 farmers of whom 79.7% were male. A significantly high proportion (77.7%) of the farmers did not use protective gear while applying pesticides. A notable percentage ate while applying pesticides (17.6%), one out of five took fluids and about a quarter smoked cigarettes. Factors found to be significantly associated with those practices were education, marital status, reporting frequent household spraying, long duration since starting to apply pesticides and farm size (p<0.05). Conclusions: Given the lack of protective behavior, it is then very important that farmers and farm workers are reminded of the hazardous nature of pesticides and the need to have their health monitored regularly. Special educational and information strategies have to focus on those with low education, who are unmarried, working on large farms and have a high frequency of applying pesticides. To enhance sustained education and supervisions, community level surveillance and supervisors could be introduced.
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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) | 0.002 | 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".