A Framework for Healthcare Resilience During Widespread Electrical Power Loss
Bibliographic record
Abstract
Healthcare delivery systems are vulnerable to a prolonged loss of electric power, particularly an extended regional or multi‐region breakdown in the electric grid. This is attributable to the reliance of acute care and ambulatory facilities on continuous electric supply for both life‐saving and vital facility support functions. We describe how a framework for disaster resilience can be applied to improve healthcare system adaptability to such scenarios. Our recommendations emphasize important preparedness efforts necessary to maintain—as best as possible—healthcare services during a period of extended regional of multi‐region electrical power loss. Specifically, we call for the development and activation of energy resilient disaster resource hospitals, the need for enhanced healthcare coalition (HCC), Medical Reserve Corps, and national disaster medical system involvement during high‐impact electric outage conditions, the necessity for a centralized federal coordination function, and public engagement to facilitate a culture of resilience to health disasters, including the extended loss of power. In order to increase preparedness, we advocate the development and implementation of pilot projects intended to enhance health sector resilience to power grid failure.
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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 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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".