Un demi-siècle d'agriculture en Grand Est : les recensements agricoles de 1970 à 2020 à l'échelle départementale
Bibliographic record
Abstract
La parution du recensement agricole 2020 (RA 2020) offre l’opportunité inédite de retracer 50 ans d’agriculture à l’échelle du Grand Est. L’approche quantitative est privilégiée : les données sont analysées à l’échelon départemental à partir de calculs élémentaires de parts et de taux de variation des différents ateliers végétaux et animaux. Des tendances lourdes émergent de l’analyse et permettent de dépasser les lectures tripolarisées de l’agriculture – bien connues en Grand Est – entre des plaines céréalières productives, des zones viticoles à forte valeur ajoutée et des espaces de maintien de la polyculture-élevage. Combinée ponctuellement à l’approche qualitative, l’analyse quantitative met au jour des configurations atypiques de territoires de firme autour de productions peu répandues dans la région. L’article souligne une coexistence des dynamiques de spécialisation versus de diversification selon l’échelle spatio-temporelle et/ou les ateliers de production analysés, qui renvoient aussi à des formes typiques d’agriculture de service ou de coteaux.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".