Perspectives from State and Regional Professionals on Rural Alaskan Water Projects (2020-2021)
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This dataset comprises anonymized transcripts from 20 semi-structured interviews with engineers, program managers, service providers, and researchers engaged in water infrastructure work in rural Alaska. Interviewees represented tribal, federal, and state agencies; private companies; nonprofit organizations; and academic institutions involved in the design, management, operation, or study of community drinking water systems across Alaska. Interviews were conducted in 2020 and 2021 and focused on identifying factors that contribute to the success or failure of rural Alaska drinking water projects. These projects face a range of persistent challenges that threaten reliable access to clean drinking water for community members. Interviews supported the following publication: Thelemaque, N., Cotherman, A., Pearson, R., Eichelberger, L., Neumann, R. B., & Kaminsky, J. A. (2022). Identifying the Built, Natural, and Social Factors of Successful and Failed Rural Alaskan Water Projects: Perspectives from State and Regional Professionals. Academic Chemical Society (ACS) Environmental Science and Technology (EST) Water. https://doi.org/10.1021/acsestwater.2c00201 File names for interview transcripts include the date of the interview, the professional role of the interviewee, and the number of years of experience they had at the time of the interview in rural Alaska water systems. Professional role categories included: - Geophysicist - Water pump service provider (abbreviated as 'pump' in file name) - Researcher in engineering, Alaskan rural water, or arctic research (abbreviated as 'researcher' in file name) - Engineer/project manager/construction manager (abbreviated as 'engineer' in file name) - Director/program manager for environmental health, drinking water, facilities, operator certification, and/or remote maintenance (abbreviated as 'director' in file name)
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Metrics Over Time
Publication Details
Subfield
Soil Science
Field
Agricultural and Biological Sciences
Domain
Life Sciences
Confidence Score
47%
Source
Scholar Data Model