How Do Non-Catastrophic Natural Disasters Impact Middle-Aged-to-Older Persons? Using Baseline Canadian Longitudinal Study on Aging Data to Explore Psychological Outcomes Associated with the 2013 Calgary Flood
Bibliographic record
Abstract
The objective of this study was to identify group-level health outcomes associated with the 2013 Calgary flood on Calgary participants (45-85 years of age) in the Canadian Longitudinal Study on Aging (CLSA). We compared baseline CLSA data collected on Calgary participants during the 6 months prior to and following the flood. Logistic regression models were created to explore whether select psychological outcomes were associated with the flood for participants categorized by evacuation status. Participants living in evacuated communities pre-flood had significantly lower levels of a diagnosed anxiety disorder than non-evacuated communities, which disappeared post-flood. Participants with higher household income were less likely to have post-traumatic stress disorder symptoms, worse self-rated mental health, and lower life satisfaction post-flood. Living alone reduced and female gender increased levels of perceived functional social support post-flood. Although natural disasters can shape research findings, the scope of the data being collected and the representativeness of impacted groups may challenge the ability to detect subtle impacts.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".