A comparative study: Accreditation of universities' disaster risk management for health promotion
Bibliographic record
Abstract
BACKGROUND: Risk management processes accreditation in emergencies and disasters can determine the effectiveness and efficiency of these processes. Universities, as the highest level of education, should provide a safe environment for educational services and activities of these people. AIMS: The present study aimed to review and compare different accreditation models for emergencies and disaster risk management in selected countries. Reaching other accreditation models together and identifying their similarities and differences, along with considering the implementation of each model, can significantly help the countries which aim to design and develop a risk management accreditation model or upgrade their models. MATERIALS AND METHODS: In this qualitative comparative study, the US, UK, Canada, Australia, Japan, and South Africa were selected based on research criteria. A literature review compared university emergency and disaster risk management accreditation models. The obtained data were collected in a researcher-made matrix, and a content analysis method was used for data analysis. Differences and similarities of selected countries in the fields of accreditation program(s), accreditation institute, start year, obligation, accredited organizations, number of criteria, criteria titles, accreditation focus, accreditation stages, number of stages, scoring method, and ranking method were compared. RESULT: Designing a local model for the accreditation of disaster risk management in universities based on the crisis management system in each country can lead to improving the level of responsiveness and quality of services in emergency situations and health promotion.
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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 | 0.002 | 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 | 0.000 | 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".