Opportunities and challenges of food policy councils in pursuit of food system sustainability and food democracy–a comparative case study from the Upper-Rhine region
Bibliographic record
Abstract
Conventional food systems continue to jeopardize the health and well-being of people and the environment, with a number of related Sustainable Development Goals (SDGs) still far from being reached. Food Policy Councils (FPCs)—since several decades in North America, and more recently in Europe—have begun to facilitate sustainable food system governance activities among various stakeholders as an explicit alternative to the shaping of food systems by multinational food corporations and their governmental allies. In contrast to the former, FPCs pursue the goals of food system sustainability through broad democratic processes. Yet, at least in Europe, the agenda of FPCs is more an open promise than a firm reality (yet); and thus, it is widely unknown to what extent FPCs actually contribute to food system sustainability and do so with democratic processes. At this early stage, we offer a comparative case study across four FPCs from the Upper-Rhine Region (Freiburg, Basel, Mulhouse, Strasbourg)—all formed and founded within the past 5 years—to explore how successful different types of FPCs are in terms of contributing to food system sustainability and adhering to democratic and good governance principles. Our findings indicate mixed results, with the FPCs mostly preparing the ground for more significant efforts at later stages and struggling with a number of challenges in adhering to principles of democracy and good governance. Our study contributes to the theory of sustainable food systems and food democracy with the focus on the role of FPCs, and offers procedural insights on how to evaluate them regarding sustainable outcomes and democratic processes. The study also offers practical insights relevant to these four and other FPCs in Europe, supporting their efforts to achieve food system sustainability with democratic processes.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".