What Japan can learn from Canada's guidelines on food and nutritional support during emergencies: A scoping review
Bibliographic record
Abstract
BackgroundProviding meals to an evacuated population is important for sustaining their health during disasters. In the 2023 wildfires in Canada, Emergency Social Services played an important role in disaster management, cooperating with restaurants. In contrast, Japan faced operational problems in disaster management during the 2024 Noto Peninsula Earthquake.ObjectiveWe aimed to investigate the national model for food service management and dietary considerations during disasters in Canada to reveal novel insights for Japan.MethodsWe conducted a scoping review to identify websites, manuals, and guidelines published between 2019 and 2024 using Google. Consequently, a nationwide manual from Canada titled 'Emergency food services: Planning for disaster' (EFS manual) was extracted, and eight nationwide guidelines or manuals from Japan were identified that contained items applicable to the EFS manual.ResultsWe found that external professional associations actively participate in emergency food services in Canada, whereas public health dietitians mainly take responsibility for food management in Japan. Volunteer organizations or professional meal provision operators, such as restaurant owners, are members of the Food Service Planning Committee in Canadian emergency food management. In Canada, a Food Service Coordinator conducts surveys on food resources that are prepared and reviews them once a year before disasters. Canada followed its national food guidelines for normal situations even in emergency cases, whereas Japan's Ministry of Health, Labour and Welfare issued nutritional reference values for evacuation shelters. The Canadian EFS manual highlights the importance of providing adequate support, including meal services, to staff for effective disaster management of evacuees.ConclusionsJapan, particularly, should utilize external professional associations from the planning stage and dietary care for staff, as in Canada. Our findings may contribute to the revision of the disaster nutrition manual for Japan to improve nutritional assistance in evacuation shelters during disasters.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".