Urban Food Strategies. Exploring Definitions and Diffusion of European Cities’ Latest Policy Trend
Bibliographic record
Abstract
Abstract Food, notably its logistics, security, quality, sustainability and social inclusiveness, is increasingly considered as a crucial element in urban settings, deserving specific institutional and strategic instruments. This is testified by the proliferation of urban food strategies, that is municipal strategic documents that various European cities have adopted during the last decade. This chapter examines the emergence and diffusion of the concept in Europe, contextualizing it in connection with broader thesis on ‘alternative’ food systems, ‘new localism’ and ‘strategic planning’, in order to unpack how the notion has been constructed. The first part of the chapter reviews the existing literature on urban food strategies, by presenting the debate over the definition of the concept and discussing the normative stance of scholars in regard to ‘alternative’ practices. After providing a working definition of urban food strategies, the second part presents an overview of their diffusion in Europe and briefly maps the historical diffusion of the model since the first appearance in Toronto in 2000. The fast adoption of urban food strategies in different urban contexts suggests the necessity of further investigations on the motivations behind the cities’ drive towards food governance. In this sense, the chapter argues in favour of a more cautious assessment of food strategies on behalf of scholars, beyond the positive enthusiasm that has been so far connected to them. In particular, the chapter calls for a critique on the political implications of food strategies, which urgently need to be assessed within strategies of city branding, and to be tested on their actual consequences on urban regeneration and development 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 | 0.011 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.016 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".