Waste Pickers Are Part of the Solution to Solid Waste Management in Senegal
Bibliographic record
Abstract
Waste pickers from the Bokk Diom organisation, working at Dakar’s Mbeubeuss landfill – in Senegal’s capital city –, continued to provide essential waste management services throughout the Covid-19 pandemic, contributing to public health, reducing environmental harm, and mitigating greenhouse gases. As with many, their incomes were impacted by the pandemic, especially those of women. However, the greatest threat to their incomes and livelihoods is the transformation of the waste management system, a process which they are excluded from. Drawing on research carried out with Women in Informal Employment: Globalizing and Organizing (WIEGO) during the pandemic, Bokk Diom was able to advocate on behalf of waste pickers and obtain pledges of inclusion in solid waste management (SWM) from national authorities. Bokk Diom and WIEGO are continuing in their efforts to attain a just transition for waste pickers.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".