During and after a landslide: it’s not just clay that suffers consequences, it’s people too
Bibliographic record
Abstract
Abstract On the evening of May 4, 1971, the population of the municipality of Saint-Jean-Vianney (Saguenay–Lac-Saint-Jean) fell victim to a severe and deadly landslide that engulfed 41 houses within minutes, creating a massive chasm and causing the deaths of 31 people of all ages. This article presents the results of a qualitative study conducted 29 years after the disaster, involving 42 adults interviewed in a semi-structured format. The participants in the study recalled the events that affected them the most, the emotions they experienced, and the consequences they faced in the months and years following the landslide. The findings show that, regardless of their level of exposure, all respondents were deeply affected by what they had experienced and felt that the event had profoundly disrupted many aspects of their lives.
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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 | 0.000 | 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 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".