Food strategies and restitution of urban agriculture illustrated by the case of selected solutions of metropolitan areas
Bibliographic record
Abstract
The purpose of the paper was to present and emphasise the importance of the concept of food strategies in creating sustainable development of metropolitan areas and restitution of agriculture. By reviewing Canadian and French solutions, among other things, an attempt was made to indicate the importance of urban agriculture in shaping sustainable development (SD) of metropolitan areas. Design/methodology/approach: In order to illuminate the phenomenon of urban strategic planning in the restitution and development of urban agriculture, a descriptive case study was adopted as the methodology of qualitative research, where the empirical basis consisted mainly of urban plans of selected cities, study of the subject literature and analysis of selected legislative acts. Findings: The presented models of coherence building at a local level show that only planning and new generation strategic plans of a metropolis that take into into account urban food systems are able to balance long-term development objectives and protect natural resources for future generations. Such a model is characterised by not only innovative methodology of planning, but also innovative operational instruments and new ways of implementation. Practical implications: using accumulated knowledge and experience in managing sustainable development of cities. Originality/value: presenting world standards in planning sustainable development of cities and emphasising the importance of urban food production and agriculture as a zone of a metropolis's natural balance.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".