Strengthening Disaster Risk Communication: Insights from Emergency Operation Centers in Saudi Arabia
Bibliographic record
Abstract
Effective risk communication is essential for coordinated disaster response, particularly among Emergency Operation Center (EOC) leaders managing crises. This study assesses the perceptions of EOC leaders in Saudi Arabia regarding key risk communication challenges, focusing on clarity, transparency, and consistency. Using a purposive sample of 95 EOC leaders, the study employed a structured survey to gather data on various aspects of disaster communication. Results indicated high ratings for the clarity and accessibility of information, though transparency and consistency scored lower, revealing gaps in cross-agency communication. Notable correlations between trust, reliability, and transparency suggest that strengthening one element may reinforce others, promoting cohesive disaster response. Qualitative responses highlighted the need for standardized protocols, real-time updates, and culturally adaptive messaging suited to the regional context. The findings emphasize practical steps, including centralized communication channels, designated spokespersons, and training programs tailored to EOC leaders’ unique needs. These measures, emphasizing clarity, consistency, and trust, can improve inter-agency coordination and strengthen disaster resilience. This study contributes to the literature on disaster management by providing insights into the Saudi Arabian context, with implications for policy and practice in risk communication.
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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 | 0.004 | 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 | 0.001 |
| Open science | 0.001 | 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".