Grassroots innovations in ‘extreme’ urban environments. The inclusive recycling movement
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
Waste pickers all over the world work innovatively to reduce the environmental footprint of cities as they struggle to meet their critical livelihood obligations. Informed by the case of waste picker organizations (WPOs) this article examines how grassroots initiatives and extreme-niche innovations are created and sustained by mobilizing resources, rationales and relations. The study is informed by a cross-national survey and in-depth interviews with WPOs in Argentina, Brazil, Nicaragua, Kenya and Tanzania, and builds upon theories of grassroots innovation movements. The findings show how operating in contexts of extreme scarcity, these grassroots organisations tap into local resources, e.g. tacit knowledge, economies of affection and other socially embedded institutional resources. Blending material and environmental rationales, contributes to expanding their audiences and to gaining further support. In such deprived urban contexts, radical and cumulative crises and events hindering residents’ livelihoods can paradoxically also spark ingenuity out of necessity, and the transformation of these settings into extreme niches of innovation. Finally, the mobilization of relations through the formation of networks linking WPOs with supportive intermediaries and global circuits of solidarity becomes another fundamental resilience strategy by which WPOs can navigate contested environments and insert their extreme-niche innovations in governmental structures. By simultaneously adopting a broad repertoire of strategies of insertion, contention, and mobilization WPO and their innovations thrive in highly constrained environments. We conclude with reflecting on how ‘ extreme’ niches of innovation − at the cracks of the formal city, economy and waste systems − can unleash the creative power of stigmatized, illiterate and neglected grassroots to experiment with new solutions in resource-poor environments.
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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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