Psychological, Physical and Behavioral Health of Adults, 3 Years After Exposure to a Train Derailment
Bibliographic record
Abstract
In July 2013, a train derailment profoundly disrupted the tranquility of the population of Lac-Mégantic for months and even years. In 2016, we conducted a representative population-based survey among 387 people from Lac-Mégantic and 413 from other municipalities with the aim to document psychological and physical health of adults exposed to the disaster. This article examines differences between 3 groups of respondents: those who were highly, moderately or not exposed to the train accident. Khi Square analyses, odds ratios and logistic regressions were used to examine differences between the 3 groups of respondents (high, moderate and no exposure). Results show that the level of exposure to this technological disaster is strongly associated with psychological suffering, post-traumatic growth, physical heath, drinking patterns, and use of prescribed and non-prescribed drugs. We can explain these results by the nature and cause of the event as well as its consequences.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".