Informal and Cooperative Recycling as a Poverty Eradication Strategy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Selective garbage collection and separation involves many of the urban poor. For them solid waste means resources and recycling becomes a survival strategy. In Brazil, almost a million recyclers perform the service of collecting, separating and commercializing recyclable material. Their work is considered mostly informal and is subject to health risks, accidents and exploitation. Some recyclers are organized in cooperatives, associations or social enterprises. These collective forms of organization provide important spaces for social inclusion and human development, by promoting meaningful work, increasing the workers’ self‐esteem and improving their living and working conditions. Resource recovery and recycling also generate net carbon credits, which need to be redirected towards this sector. The recent introduction of waste to energy technology is perceived as a threat to the recyclers’ livelihoods. Incineration does not generate income, produces environmental contamination and competes with other forms of waste management. Action oriented, participatory research with recycling groups in Brazil supports the argument that organized recycling generates social, economic and environmental benefits and radically addresses poverty reduction. Remunerating the recyclers for their service and considering the environmental gains of their work ( Clean Development Mechanism ) tackles the Millennium Development Goal of poverty alleviation. Finally, participatory waste management has an important role to play in promoting necessary drastic changes towards a closed looped economies and more sustainable communities on a global scale.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 it