Séisme et reconstruction psychique : les piliers de la résilience face au séisme
Bibliographic record
Abstract
Les catastrophes naturelles infligent des dommages importants à la santé psychologique des individus. De nombreux facteurs sont connus pour favoriser la résilience psychologique post-catastrophe. Le but de la présente recherche est d’examiner l’influence des facteurs de résilience sur le processus de rétablissement des victimes du séisme d’Al Haouz. Au total, 51 entrevues semi-directives ont été menées auprès de personnes sinistrées, environ neuf mois après la survenue de la catastrophe. Selon les résultats, plusieurs facteurs favorisent la résilience psychologique, notamment le recours à la religiosité, le soutien social, le soutien familial, la redéfinition des priorités existentielles, la culture du risque et le sacrifice de soi. Il semble que les variables intrapersonnelles et interpersonnelles constituent des ressources importantes qui fonctionnent en tandem et façonnent le processus de résilience péri- et post-catastrophe.
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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 | 0.004 |
| 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 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".