Navigating the Fault Lines in Civic Food Networks
Bibliographic record
Abstract
Civic food networks have emerged as a civil society–driven response to the social, economic, and environmental shortcomings of the industrial food system. They are differentiated from other forms of alternative food networks in that they emphasize cooperation over independence, focus on participatory democratic governance over hierarchy, and serve both social and economic functions for participants. Yet there is little understanding of the processes of cooperation, particularly among farmers, in civic food networks. In this five-year action research project we documented the development of a farmer-driven civic food network in southern Manitoba on the Canadian Prairies. We explore the relations among farmers to better understand the potential of civic food networks to contribute to a more resilient and locally controlled food system. Our findings highlight the tensions and power dynamics that arise through the processes of re-embedding farmers in more interdependent relations. Fractures occurred in the group when negotiating the diverse needs and values of participants, which manifested in disputes over the balance of economic and extra-economic organizational pursuits, over the nature of the cooperative distribution model, and over quality standards. Asymmetrical power relations also emerged related to gender and generational differences. Although social embeddedness and civic governance did lead to enhanced relations and trust, these positive outcomes were unevenly distributed and coexisted with feelings of distrust and acrimony. In order to realize their full potential, proponents of civic food networks must confront difference in order to embrace the strength that comes from diversity in the process of building more resilient, and civic, food networks.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.029 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".