Uncontrolled dumping and the initiative of women waste pickers
Bibliographic record
Abstract
Cotonou faces a long-standing waste disposal crisis as most waste ends up in informal dumpsites, in Lake Nokoué, or in the sea. This waste pollution has led to water-borne diseases, biodiversity loss, and clogged sewers. The Dantokpa market, a major waste generator, has no adequate waste management system, and much of its waste is illegally dumped. Cotonou produces 700 to 800 tonnes of waste daily, with only 100 tonnes processed in the Ouèssè landfill. The remainder is uncollected, exacerbating environmental and public health problems. The Tori-Avamé landfill explosion in 2016, killing 18 people, brought to light serious safety violations. Despite the dangers, informal waste pickers continue to work under hazardous conditions. The Association de Femmes Recuperatrices du Benin, one of the main informal groups representing female waste pickers, or gohotos, was founded in 1997 to focus on recycling initiatives and improving women’s lives. Gohotos buy and sell recyclables, particularly bottles, and provide informal waste collection for about 70% of Cotonou’s population. They have developed a recycling centre and have gained international recognition, supported by Oxfam-Québec. The group still faces challenges, including a lack of government support, health insurance, and basic equipment. They continue to empower themselves, despite the challenges, through community-building and self-help initiatives.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".