The rise of urban agriculture in Belgium: feeding the population through investing in two large cities: Brussels-Capital and Liège
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The loss of farms is problematic in Belgium, particularly in Wallonia (68% loss between 1980 and 2015) and in the Brussels-Capital Region and access to land is a real challenge for farmers to deal when setting up their farms. Recently, however, there has been a real increase in awareness of the importance of agricultural activity and land on the part of public authorities and especially of citizens who are trying to regain control of their food. These citizens are looking for a healthier and safer food in the face of the shortage of agricultural land in a densely populated country. The smallest interstices of the cities are occupied to set up innovative agricultural projects such as in Brussels and Liège where vegetable gardens and a Food Land Belt is developing to feed the populations of the cities. These agri-urban projects are the work of the citizens themselves, who take the initiative themselves to realize these innovative actions by pooling their knowledge and tools centered on new agricultural production models. We highlight the actions taken by certain segments of the population in the cities of Brussels and Liège where food, social and environmental issues have become a concern for consumers who invest in the green spaces left vacant compared to what is being done in other countries such as Canada or France, for more than a decade.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it