Building Autonomous Power: Solidarity Networks in Precarious Times
Bibliographic record
Abstract
From COVID-19 to the so-called labour shortage of late 2021, the past three years have revealed a renewed discourse on labour markets and working conditions. Alongside this discourse, workers in a variety of industries have been organising to fight the rollbacks, redundancies and concessions imposed in response to the pandemic and its related financial crisis. From Amazon warehouse workers to hospitality workers to informally employed platform workers, the global precarious are rising up. In addition to traditional labour movement tactics, one tool that has proven powerful and flexible in the COVID period is the autonomous solidarity network. Built from the model of the worker centre, a labour solidarity network is conceived of as a decentralised grouping of workers, organisers and allies, usually operated virtually and at arms-length from formal union structures. Following the methodological foundation of workers’ inquiry and using the tools of strategic labour research and participatory action research, this article reports on interviews with workers and organisers involved with worker centres and solidarity networks, distilling their experiences and observations into a set of common practices that characterise worker organising efforts taking place in a number of Canadian workplaces, including hospitality, migrant work programs, platform services and artisanal industries. In addition to traditional labour movement tactics, one tool that has proven powerful and flexible in the COVID period is the autonomous solidarity network. Built from the model of the worker centre, a labour solidarity network is conceived of as a decentralized grouping of workers, organizers and allies, usually operated virtually and at arms-length from formal union structures. Following the methodological foundation of workers’ inquiry, this article reports on interviews with workers and organizers involved with worker centres and solidarity networks, distilling their experiences and observations into a set of common practices that characterize worker organizing efforts taking place in a number of Canadian workplaces, including hospitality, migrant work programs, platform services, and artisanal industries.
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How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".