Expansion of the Waste-Based Commodity Frontier: Insights from Sweden and Brazil
Bibliographic record
Abstract
Waste is a valuable commodity and remains a livelihood source for waste pickers in the global South. Waste to Energy (WtoE) is often described as alternative to landfilling, as it provides cheap fuel while making waste disappear. In some European cities, this method has evolved into an impediment, slowing down the adoption of more sustainable technologies and waste prevention. These plants typically strain municipal budgets and provide fewer jobs than recycling and composting, thereby inhibiting the development of small-scale local recycling businesses. We applied the idea of ‘waste regime’ with an interdisciplinary and situated lens to provide insights to the following questions: How do different political developments in Brazil and Sweden, frame and reframe waste incineration and energy recovery, in the context of sustainability and waste management on local, regional and national levels? What forms of resistance against WtoE exist and what are the arguments of these protagonists? We evaluated the impact of WtoE and compare it with other waste management options with regard to CO2 balances and general environmental and social impacts. We conclude by suggesting more socially and environmentally appropriate ways of waste management, particularly for the context of global South cities.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".