Water Vulnerability in Arctic Households: A Literature-based Analysis
Bibliographic record
Abstract
There is an urgent need to understand the contextual factors that influence water vulnerability of households in the Arctic. To evaluate the existing knowledge of Arctic household water vulnerability, this paper presents the results of a narrative review with a systematic search. The review identified 112 documents, including peer-reviewed articles, reviews, book chapters, proceedings papers, and meeting abstracts. The documents were analyzed for the main factors affecting water vulnerability in Arctic households, which fell into two categories: biophysical factors and anthropogenic factors. Within the biophysical category, the majority of documents noted climate change impacts on freshwater supplies and water systems, followed by attention to extreme weather and the seasonality of water supplies. Within the anthropogenic category, the vast majority highlighted infrastructure as the primary issue affecting water access, followed by economic, governance, socio-cultural, and demographic factors. Through these diverse influencing factors, this review situates the discussion of household water vulnerability in the Arctic in a more nuanced light. The categories illuminate patterns between factors, which can worsen, assuage, or mitigate water vulnerability. The complex relationships between these factors influence the degree and nature of water vulnerability in Arctic households. In order to successfully address household water vulnerability in the Arctic, these factors and their dynamic relationships must be considered in freshwater policy and management frameworks.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.048 | 0.043 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".