Co-operative Development, Policy, and Power in a Period of Contested Neoliberalism: The Case of Evergreen Co-operative Corporation in Cleveland, Ohio
Bibliographic record
Abstract
After the financial crisis in 2008 and amid growing concerns about climate change, interest in systemic alternatives to neoliberal capitalism is growing. This cultural shift helps explain the enthusiasm from political elites, media, and academics that greeted the launch of Evergreen Co-operative Corporation in 2009. Based in Cleveland Ohio, Evergreen is a network of worker-owned co-operatives with scalability and replicability woven into its design. But how warranted is the broad-based enthusiasm around Evergreen? Is this a model that can be replicated across North America as its founders suggest? Based on site visits and stakeholder interviews, we argue that there are important limits on desires to reproduce the “Cleveland Model.” However, its ambitions for scalability and replicability position it to contribute to the important project of movement building that can facilitate the policy change needed to scale up the co-operative alternative.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.050 | 0.037 |
| Scholarly communication | 0.017 | 0.009 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.006 | 0.008 |
| 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".