Integration of waste pickers in waste management systems worldwide: A review of approaches and outcomes
Bibliographic record
Abstract
Waste pickers (WPs) are essential for the circular economy and sustainability, as they help cities and producers fulfil their responsibilities, promoting recycling. However, they are usually not recognised and remunerated, despite their integration being widely advocated in the literature. Still, research is needed to identify different integration formats, actors and results worldwide, which is the aim of this article. A systematic literature review following Preferred Reporting Items for Systematic review and Meta-Analysis (PRISMA) was conducted, including journal articles and grey literature. Sixty-three documents were selected, of which 78% were about Latin America, and one unique case was from a high-income country, Canada. Integration interventions were divided into eight categories according to their characteristics: household selective collection and sorting programmes; payment for environmental services; relocation from dumpsites; extended producer responsibility systems; purchasing systems; services for the private sector; individual hiring and individual support. The results show few cases with payment for the service provided (39%) and focused on individuals instead of groups (11%). Although progress has been made, these initiatives can still be improved. This article defines the concept of WP integration and offers recommendations for enhancing outcomes. These results provide decision-makers with a range of strategies to be prepared for more inclusive waste management.
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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 | 0.019 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".