Stresseurs et impacts sur la santé mentale des victimes : le cas des inondations au Québec
Bibliographic record
Abstract
Les personnes touchées par les inondations font face à divers stresseurs qui augmentent leur niveau de stress, nuisent à leur santé mentale et ralentissent leur rétablissement. Cet article présente les résultats d’une étude mixte menée auprès de 680 répondants touchés par les inondations du printemps 2019 au Québec. L’objectif était d’identifier les stresseurs vécus et de mesurer leurs effets sur la santé mentale, notamment sur les symptômes dépressifs, l’anxiété, la détresse psychologique et le trouble de stress post-traumatique. Les résultats démontrent que les stresseurs, qu’ils soient primaires ou secondaires, ont des impacts significatifs sur la santé mentale des participants.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 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".