Explaining informal workers’ organizing experiments: A cross-country study of Brazil, China, and India
Bibliographic record
Abstract
Informal workers’ recent organizing efforts deserve our attention. They have defied the odds and launched alternative models that are more relevant to contemporary structures of globalized and neoliberal production than earlier industrial union-based organizing efforts. While some have succeeded in increasing protections and others have failed, all have relied on informal workers’ willingness to experiment with new organizational forms, rules, and definitions of work, identities, regulations, sectors, and populations. It is these experiments, we argue, that are crucial to ensuring a more just future for global labor. Drawing from fieldwork data collected among informal workers’ organizations in the garment manufacturing sectors of Brazil, India, and China, this article builds two hypotheses to explain the conditions that shape, facilitate, and/or hinder experimentation among informal workers of the global South. First, we propose that political conditions from above—namely, decentralized political administration/federalism, competition among political parties, and support from ruling governments and/or industrial unions—helped foster the necessary space for informal labor to undertake organizational experiments during the turn of the millennium. These conditions, in turn, interacted with nation-specific legacies of labor organization from below to shape particular forms. Second, we propose that changes in the political conditions from above can erode the space for labor’s organizing experimentation, but that the legacy of labor’s organizational experiments from below can also resist and reshape those very changes in political conditions. These findings offer hope for the possibilities of labor revitalization even under neoliberalism, but also a warning about the likely roadblocks to that revitalization.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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 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".