Energy Service Security for Public Health Resilience: Perception and Concerns in Western Upper Peninsula of Michigan<sup>☆</sup>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The Western Upper Peninsula of Michigan includes six rural counties and one Tribal Nation. The region is characterized by long winters, legacies of the extractive mining economy, and the infrastructural features of extreme rurality, including aging housing and low health service density. The region also faces exceptionally high electricity prices. There is limited research on the public health implications of energy service disruption in rural regions resulting from the increasing intensity and frequency of weather events caused by climate change. This article presents research findings examining the readiness of health facilities in this area to manage the rising intensity, severity, and frequency of severe weather that could disrupt energy services. The study also considers how this knowledge can guide decision‐making to improve energy service access and maintain resilient public health services in the region. This exploratory study utilized a qualitative approach that combines semi‐structured interviews with public health stakeholders and a short survey to triangulate the findings from health facilities. Given the pivotal role of dependable energy services in community health, these findings underscore the community's perception of self‐reliance as both an asset and a hurdle. This perception aligns with the realities of rural communities at the “end of the line” regarding critical infrastructure, which also serves as a formidable barrier to social organization and infrastructure access during energy service disruptions that can severely impact public health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 it