Permafrost Food Storage Monitoring and Vulnerability Assessment in Utqiaġvik, Alaska
Bibliographic record
Abstract
Traditional Iñupiaq sigḷuaq are cellars excavated into permafrost for storage of large quantities of game, fish, and other foodstuffs harvested for subsistence. Permafrost provides both a cultural and regulatory ecosystem service to Arctic peoples. A cellar thermal monitoring program in Utqiaġvik (formerly Barrow), Alaska, documented catastrophic flooding, collapses, and other issues in these cellars related to warming climatic conditions, community functions, and development. This paper provides an update on the Utqiaġvik monitoring program, which was operational from 2005 to 2019. All five monitored cellars exhibited stable to warming mean annual internal temperatures over the period of observation. Two cellars flooded, another was abandoned because of sloughing walls, and two were functioning until the COVID-19 pandemic. Based on experiences gained from the 14-year Utqiaġvik monitoring program, we conduct a vulnerability assessment using the source-pathway-receptor-consequence (SPRC) model and identify several vulnerability reduction measures. We recommend the SPRC model to aid evaluation of specific vulnerabilities of cellars and other traditional frozen infrastructure, and to improve future monitoring methods and products through increased community participation. Any attempt to provide data for community-resilience decisions should start with identifying and communicating process components, thereby bridging stakeholder learning and responses (their “heuristics” in the SPRC model) and science-based knowledge.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".