Climate change, mass casualty incidents, and emergency response in the Arctic
Bibliographic record
Abstract
Abstract Acute emergencies have been neglected in efforts to understand and respond to the transformational climatic changes underway in the Arctic. Across the circumpolar north, social-technological changes, extreme weather, and changing ice conditions threaten lives and infrastructure, increasing the risk of mass casualty incidents (MCIs), particularly as they impact transportation systems including global shipping, aviation, and community use of semi-permanent trails on the ice, land, and water. The Arctic is an inherently dangerous environment to operate in, and due to living in permanent settlements and the uptake of mechanised modes of transportation and navigation technologies, people’s exposure to risks has changed. In responding to potential MCIs, emergency response systems face challenges due to remoteness, weather, and changing environmental conditions. We examine emergency response capacity in the Arctic, focusing on search and rescue and using examples from Canada and Greenland, identifying opportunities for enhancing emergency response as part of climate adaptation efforts.
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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 | 0.006 | 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 | 0.001 |
| 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".