Dealing with Environmental Disaster: The Intervention of Community Emergency Teams (CET) in the 2010 Israeli Forest Fire Disaster
Bibliographic record
Abstract
In December, 2010, a large forest fire broke out in the Carmel Forest in Israel near the city of Haifa and spread throughout the communities of the Carmel Seashore Regional Council. The fire left forty-four casualties and thousands of square kilometers burned. This paper describes the effective performance during the fire of Community Emergency Teams (CET) established and trained during the previous year in residential areas, to be ready to react in any community emergency, whether security situation or natural disaster. The CETs were organized according to a community preparedness model developed by the Community Work Service of the Ministry of Welfare to provide an immediate local response until official forces arrive at the scene. CETs alerted and enlisted residents, provided information, and guided them through evacuation as well as taking care of private and public property and participating in fighting the fire. The success of CETs is due to three identifiable stages: First, volunteer training and preparation to gain personal and community resilience. Second, cohesive and organized action taken by the CETs during the four day blaze. Third, the recognition and reinforcement gained by volunteers and residents at the community level. It is suggested that the model be applied to as many communities as possible for a fast suitable reaction in any type of emergency situation in Israel.
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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 | 0.001 | 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".