Perceptions on pesticides: Knowledge, attitudes and practices of residents in Trinidad and Tobago
Bibliographic record
Abstract
Extensive pesticide use in Trinidad and Tobago (T&T) raises concerns for human and environmental health. Therefore, this study sought to assess the general knowledge, attitudes and practices of T&T residents on pesticides and related topics. Using convenience (non-probability) sampling, a questionnaire was administered to residents of Trinidad (N = 572) and Tobago (N = 68). Most respondents (93.44%) had insufficient knowledge on pesticides and application protocols but had supportive attitudes (95.94%) that acknowledged pesticides as harmful, and positive perceptions toward eco-friendlier approaches (IPM, organic farming). Poor practices (97.5%) were prominent, including heavy pesticide reliance (>70.0%), no PPE during pesticide handling (48.76%) and minimal use of IPM (15.31%) and biocontrol (12.50%). User knowledge gaps and malpractices can inform local state entities in designing effective public outreach initiatives for promoting adoption of safer pest management practices.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".