Inclusive recycling movements: a green deep democracy from below
Bibliographic record
Abstract
This paper examines the multiple strategies articulated by grassroots recycler networks to bring about socioenvironmental change. The paper shows how these networks are an emblematic case of grassroots governmentality, whereby urban poor communities contribute to building more inclusive environmental regimes by developing technologies of power more typical of the powerful. These technologies include enumeration, with its resulting self-knowledge; the production of discourses and rationalities of social inclusion and environmental sustainability; and engagement in open and diverse alliances, at times with actors holding apparently antagonistic interests. The paper also reveals how recycling networks are a representative case of deep and green democracy. It is deep democracy, as grassroots networks strive to gain deep and true representativeness in their territories. It is green democracy, as it illustrates alternative pathways to environmental governance that is not limited to state and global organizations, but that also includes a range of control techniques emanating from the communities themselves.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.017 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".