Cultivating Alliances: The Local Organic Food Co-ops Network
Bibliographic record
Abstract
Although social movements can lose their way in neoliberal times, building alliances can help them to leverage their strengths and overcome their weaknesses, thus avoiding co-optation and “mission drift.” One example of this strategy can be found within the co-operative movement: the Local Organic Food Co-ops Network in Ontario. A pilot study of six co-operatives in this organization reveals that they cultivate alliances in four ways: among member co-ops, through the creation of the network, with other types of organizations, and with other social movements. These alliances strengthen the co-operative movement, help to make the politics of alternative food systems work, influence the economy toward co-operation, and open up possibilities for establishing and maintaining a more sustainable food system. RÉSUMÉ Les mouvements sociaux, bien qu’ils puissent s’égarer à l’ère du néolibéralisme, peuvent établir des alliances afin de profiter de leurs atouts et surmonter leurs faiblesses, évitant ainsi la cooptation ou les déviations. On retrouve un exemple de cette stratégie d’alliance dans le cadre du mouvement coopératif en Ontario : The Local Organic Food Co-ops Network. Une étude pilote de six coopératives faisant partie de cette organisation révèle que celles-ci créent des alliances de quatre manières différentes : entre coopératives membres, grâce à la création du réseau même, avec d’autres types d’organisation et avec d’autres mouvements sociaux. Ces alliances renforcent le mouvement coopératif, aident à faire fonctionner les systèmes d’alimentation alternative, encouragent la collaboration économique et contribuent à établir et maintenir un système d’alimentation plus durable.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".