Social movements in the context of crisis: waste picker organizations as collaborative public partners in the context of the COVID-19 pandemic
Bibliographic record
Abstract
Social movements are purposeful, organized groups of people addressing the creation and reproduction of inequality, rights and access issues, seeking to transform sectoral policies. In the context of the COVID-19 pandemic, social movements have been acting in articulation with government and private companies and through other actions formulated within their networks, as service deliverers to the poor and vulnerable populations most heavily affected, often filling a gap created by unfulfilled policies. Our research with waste picker organizations in Brazil illustrates how their struggle for recognition has taken action in this context. Academic and government documents, social media and online material (blogs, posts, websites, etc.) and virtual meetings inform this research. We found that multiple actors have contributed to mitigate the urgent needs of waste pickers during the pandemic, but that at the same time, pre-existing challenges in waste management and the lack of wide-ranging social and economic inclusion have been further intensified.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.021 | 0.023 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.002 | 0.021 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".