Proposition d’une trame de recherche pour appréhender la capacité d’adaptation au changement climatique
Bibliographic record
Abstract
Il est une idée reçue selon laquelle les communautés des pays en développement ont fatalement de faibles capacités d’adaptation au changement climatique. Prenant le contre-pied de cette affirmation, parce qu’elle n’est pas toujours vraie et parce que la considérer comme telle induit des biais dans le processus d’identification de stratégies d’adaptation, ce texte défend l’idée que les connaissances actuelles sur ce qui fonde la capacité d’adaptation d’un territoire donné sont encore insuffisantes. Il existe ainsi un manque de maturité sur cette question qui est à relier à un défaut de structuration en termes de recherche scientifique. C’est pourquoi nous proposons ici quatre grandes pistes de recherche pour améliorer l’approche scientifique de la capacité d’adaptation. Ces pistes sont ensuite replacées dans un cadre théorique plus large reposant sur l’identification de trois dimensions d’adaptation et sur la mise en perspective de trajectoires d’adaptation.
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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 | 0.029 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.019 |
| Scholarly communication | 0.013 | 0.020 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".