Trajectoires et adaptations à une crise multiple: Port-au-Prince depuis le séisme du 12 janvier 2010 au travers des concepts d’exit, voice, loyalty et apathie
Bibliographic record
Abstract
Le séisme du 12 janvier 2010 a ravagé Port-au-Prince, causant la mort de 250 000 personnes, un million de blessés et des centaines de milliers de sans-abris. Cette situation est essentiellement liée à la pauvreté, mais aussi à des choix d’urbanisme, repoussant les plus démunis à s’installer dans des quartiers précaires. La lecture des enjeux territoriaux à travers le modèle exit-voice and loyalty d’Albert Otto Hirschman permet de mieux appréhender les stratégies des personnes sinistrées. À la suite du 10 janvier, le séisme a engendré un dysfonctionnement dans les stratégies spatiales, entrainant des dynamiques de défection, de mobilité (exit), de protestations (voice), de fidélité (loyalty) et enfin d’apathie dans un contexte de crises multiples (environnementale, sanitaire, sociale, économique, politique) marqué par une grande individuation des trajectoires.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".