Editorial: The Cooperative Advantage for Community Development
Bibliographic record
Abstract
Empirical evidence has shown that cooperatives are diverse organizations that efficaciously address a plurality of socio-economic needs. Cooperative organizations are effective in provisioning for myriad life needs, and do so in more democratic and sustainable ways than investor-owned firms. Rooted in the unique principles and values that distinguish them from other business types, cooperatives, in a nutshell, embody what has been called “the cooperative advantage”. This special issue of the Journal of Entrepreneurial and Organizational Diversity, “The Cooperative Advantage for Community Development”, was organized to highlight the myriad roles that cooperatives can and do have in protecting and developing communities, as well as the possible tensions and challenges that emerge in the process. Including seven articles from established and upcoming cooperative studies scholars, the special issue critically assesses diverse experiences of co-ops deployed for community development. Via papers engaged in case study approaches, political economy perspectives, critical historical research, and qualitative and quantitative methods, this special issue of JEOD critically reflects on and contributes to understanding the role of cooperatives in grounding bottom-up and locally based community development.
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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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.019 | 0.020 |
| Insufficient payload (model declined to judge) | 0.011 | 0.008 |
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".