“It’s Good to Always Have a Plan”: A Qualitative Study of Canadians’ Preparedness During Power Outages
Bibliographic record
Abstract
OBJECTIVES: Power outages can lead to food-borne and water-borne illness risks for consumers if proper protective measures are not taken at home. The purpose of this study was to understand the behaviors of Canadians related to food and water safety preparedness at home during power outages and floods. METHODS: A qualitative descriptive study was conducted, consisting of 6 virtual focus groups, each with 8 people, in July 2023. Participants were selected from geographically dispersed locations in Ontario, Canada that had experienced power outages due to weather events. Thematic analysis was conducted to generate key themes. RESULTS: Four themes were generated related to participants' food and water safety preparedness: 1) trusted information sources and lived experiences; 2) support and resources; 3) factors beyond one's control; and 4) differences in psychosocial determinants. CONCLUSIONS: Effective risk communication targeting misconceptions, incentivization programs, and community resilience planning may help prevent or reduce enteric illness risks during such emergencies.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.027 | 0.014 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".