Politiques et institutions à l’appui des petites exploitations agricoles
Bibliographic record
Abstract
RésuméCet article défend l'idée que les petites exploitations agricoles doivent être placées au cœur du processus de développement, principalement dans les pays du Sud, notamment parce que la moitié des populations qui, dans le monde, souffrent de la faim, habitent des zones rurales et disposent de moins de 2 hectares, et parce que près de 2 milliards d'êtres humains dépendent de l'agriculture familiale. L'auteur, éminent représentant de la FAO, préconise l'insertion de la petite exploitation dans les circuits agro-industriels. Il s'agit de construire une politique différente, qui vise à rapprocher les petits agriculteurs des marchés en développant une chaîne de valeur (c'est-à-dire des arrangements contractuels au sein des chaînes de valeur agro-industrielles) et en proposant des stratégies de transition.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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; both teacher heads agree on what is shown here.
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".