La Ceinture alimentaire liégeoise: systéme innovant pour nourrir les populations locales
Bibliographic record
Abstract
Food supply is increasingly central to many questions, including both environmental and social issues; interest in the sustainability of food production systems is continually increasing. Many consumers have become very critical of the practices of modern productivist agriculture, inherited after World War II in order to defeat the "scourge of hunger" and supported later by different government policies. These practices have been increasingly rejected in rich countries by consumers more favorable towards local agriculture that also contributes to better product traceability, a key factor for many consumers. This trend also favors certain agronomic advances to mitigate the negative externalities of these productivist agricultural practices, notably negative environmental impacts and their implications for public health. In relation to this, some innovative systems have been set up, putting into practice the sustainability of agricultural practices such as the Ceinture Aliment-Terre of Liège, where since 2012 a healthier agriculture has developed through agroecology. The networks have encouraged the development of an alternative model, that is ecologically intensive, focused on short circuits, made up of diversified "micro-farms" which also give new life to conventional farms, involving the development of a very extensive model focused on a type of bio-grazing, through the purchase and development of their products through short circuits. This innovative model is also innovative from the productivity and social points of view. To demonstrate the innovative nature of food production in the Ceinture Aliment-Terre of Liège, we propose a comparative analysis with several other 'green' belts in the world: ex. London and Ottawa where other functions of these spaces have become more important than the food production function and others where the food issue has always been crucial (e.g. Toronto and Paris).
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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 | 0.012 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".