Mesures de compensation écologique : risques ou opportunités pour le foncier agricole en France ?
Bibliographic record
Abstract
Compenser revient à équilibrer un effet par un autre : les mesures de compensation obligent un aménageur à compenser les effets négatifs de son projet. Deux types d’approches sont envisagées, la première est fondée sur la demande de compensation, dans ce cas l’aménageur cherche des surfaces sur lesquelles il pourra compenser son emprise ; la seconde est axée sur l’offre de compensation, dans cette approche un prestataire sécurisera des terrains, au moyen d’acquisitions ou de contrats durables. L’analyse de la règle du jeu et des modalités de mise en œuvre de la compensation écologique permet de vérifier la cohérence de ces mesures avec les politiques foncières territorialisées. Les aspects fonciers et les notions d’anticipation et de concertation avec le monde agricole apparaissent comme les déterminants principaux de l’efficacité de ces mesures.
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 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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".