Des archipels en péril ? Les Maldives et les Kiribati face au changement climatique
Bibliographic record
Abstract
Cet article propose une lecture originale de la vulnérabilité des territoires aux risques naturels liés à la mer. À partir de l’analyse des cas des archipels coralliens des Kiribati (océan Pacifique) et des Maldives (océan Indien), il place au cœur de la démarche la notion de « système de ressources », fondée sur les caractéristiques à la fois physiques et anthropiques de ces pays. Ce faisant, il montre quelles interactions jouent aujourd’hui, qui expliquent le caractère systémique de la vulnérabilité, et en quoi le changement climatique accentuera ces jeux de rétroactions. Cela amène les auteurs à voir les États coralliens comme des cas éclairants sur les impacts qui risquent d’affecter d'autres communautés littorales de par le monde, et comme des précurseurs de stratégies concrètes d’adaptation au changement climatique, par-delà leurs spécificités.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".