Flexibilité adaptative et gestion du risque : étude de cas des inondations dans l’estuaire de la Gironde (France)
Bibliographic record
Abstract
Face aux risques d’inondation, les approches actuelles associent mesures relevant du génie civil et hydraulique et mesures relevant de la gouvernance. Les mesures de gouvernance sont, souvent, dans un contexte d’adaptation au changement climatique, associées, en théorie, à l’avantage d’être flexibles, révisables chemin faisant. Or, leur déploiement en Gironde, depuis l’évènement Xynthia, et leur association aux mesures, physique de protection, préexistantes soulève certaines interrogations. Perçues autrefois comme des mesures auxiliaires, les mesures de gouvernance dominent, aujourd’hui, les pratiques de gestion des risques d’inondations. Cet article montre que la transition d’une gestion relevant du génie civil vers une combinaison de mesures physique et de gouvernance se fait, pour les acteurs ruraux concernés, au détriment de la flexibilité associée, en théorie, à la gouvernance. Nous analysons la combinaison actuelle entre ces deux types de mesures à la lumière des incertitudes futures liées aux changements climatiques.
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 | 0.002 | 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 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".