Access to Water Service Modalities in Rural Alaska: Understanding Community Experiences and Perceptions
Bibliographic record
Abstract
Households in rural Alaska rely on various water service modalities to meet daily needs. The level of service provided impacts end-users’ ability to access and benefit from their services. Furthermore, the degree of responsibility placed on end-users for the collection, storage, and maintenance of systems varies by water service modality. Centering end-users’ experiences and preferences in water management helps ensure that water infrastructure solutions align with community needs, priorities, and capabilities. To that end, we compare end-users’ experiences with different water service modalities and perceptions of service in the Yukon-Kuskokwim Delta, one of the most underserved regions in the United States. We then explore associations between experiences and sociodemographic and geographic community characteristics to identify potential inequities or factors impacting end-users’ access to water. We conducted a qualitative content analysis of 41 semistructured interviews with 50 end-users residing in the Yukon-Kuskokwim Delta. Findings show that end-users frequently struggle with service disruptions and affordability, especially hauled water users. End-users also expressed aesthetic concerns related to the taste of chlorinated water, leading them to use potentially unsafe water service modalities for consumption. Better understanding of public perceptions allows us to center community needs when improving access to water services.
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".