Bibliographic record
Abstract
There are several categories of urban agriculture which need to be distinguished if we want to efficiently feed urban inhabitants with local agricultural produce while benefiting from other functions filled by urban agricultural landscapes: namely, eco-systemic functions or ecological and social functions. The second function will focus on methods to regulate unbuilt land in urban areas which have virtually no regulations and others which have strict controls preventing construction. The last will consist of possibilities to build, what I would refer to as, urban agricultural commons: in other words, tangible and intangible resources produced with farmers and gardeners for the inhabitants; for their local consumption and for the quality of the living environment, based on a political principle for common action. The concept of common is derived from the works of socioeconomist E. Ostrom (1990; [1]) and French philosophers P. Dardot et C. Laval (2014; [2]): “What is built in common”. It was applied to urban agriculture and landscape (Donadieu, 2012, 2014; [3,4]). The concept of urban agriculture has been used worldwide in the last twenty years by researchers, especially in France by A. Fleury (2005; [5]) and P. Donadieu(1998; [6]), in Mediterranean regions (Nasr and Padilla, 2004; [7]), in Asia, Africa and North and South America—all through the publications of the Resource Centres Urban Agriculture & Food Security (RUAF; [8]).
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.
How this classification was reachedexpand
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".