Everyday circularities: perspectives from the Global South
Bibliographic record
Abstract
To highlight critical perspectives on the Circular Economy (CE) this conversation with Manisha Anantharaman and Sonia Dias considers often-overlooked Global South perspectives on everyday dynamics of circular transformation. In this conversation, we, Mary and Kersty, chat with Manisha (Sciences Po), a scholar in critical approaches to sustainability and circularity, and Sonia, a sociologist who works for WIEGO (Women in Informal Employment: Globalizing and Organizing), about key issues and debates concerning circular change that emerge from their work in India and Latin America. Our conversation spans the broader political and economic contexts of the CE and the necessity of situating everyday circular practices within this framework of unequal access. Beginning with an exploration of the ‘circularity divide’ (Barrie et al, 2022), in which CE initiatives can deepen inequalities if not carefully approached, we discuss the crucial role of informal workers in the Global South and the importance of inclusive, context-specific approaches to circularity. We then explore the differences and similarities in consumption dynamics across settings; the role of the household as a critical scale of analysis; and the diverse domestic experiences within these settings. Finally, we discuss the significance of DIY infrastructures and the informal economy in creating and sustaining the systems of provision essential for enacting circularity, as well as the role of scholarship in supporting political action for inclusive circular change.
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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 | 0.014 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.029 | 0.073 |
| Scholarly communication | 0.019 | 0.025 |
| Open science | 0.002 | 0.022 |
| Research integrity | 0.008 | 0.013 |
| 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".