Assessment of occupational hazards facing waste pickers to support a proper closure of a large open dump
Bibliographic record
Abstract
Waste pickers are workers exposed to several occupational risks. This cross-sectional study investigated hazards associated with occupational accidents among waste pickers in the largest open dumpsite in Latin America before its closure. A survey was conducted with 999 waste pickers, collecting data on accidents and work characteristics. Among those interviewed, 686 (68.7%) of waste pickers reported having suffered accidents at work. Of these, 68.7% of them were related to exposure to sharp objects, and 62.5% were unable to work due to the accident. Work shift and work environment were significantly associated with accidents ( p < 0.001). It indicates that workplace hazards are stronger predictors of accidents than personal characteristics. This article demonstrates the necessity for integrated and multi-sectoral strategies and surveillance systems that monitor environmental, animal and human health indicators aligned with the One Health approach in municipal solid waste management. This epidemiological study provides data to support dump closure in similar contexts, especially in countries in the Global South.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.006 |
| 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 teacher head, 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".