JOURNAL ARTICLE

Sustainable Arthurdale: A Reevaluation of a 1930s Planned Community.

  • Published In: Journal of Appalachian Studies, 2023, v. 29, n. 1. P. 47 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Galford, Greg; Tucker, Lisa; Martin, Lou 3 of 3

Abstract

The Great Depression affected Appalachian towns with severe economic distress and dislocation. This research focuses on a New Deal experiment in sustainable housing initiated by Eleanor Roosevelt. Early in her husband's administration, she championed the design and construction of the planned community of Arthurdale, West Virginia. Composed of single-family homes built during three phases with a central complex of shared services, the planned town of Arthurdale has retained connections to several original residents and maintains a strong sense of community and belonging. This research explores the community design components of Arthurdale, coupled with the sustainable features inherent in the houses and its approach to sustenance farming, and considers the impact on the long-term success of the residents. For this work, a mixed-methods approach was used with an initial quantitative survey and a subsequent focus group. Survey results indicated that themes of sustainability, community, and education were values that were uniquely shared by original town residents and subsequent generations. These values can affect contemporary models of sustainable community development. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Appalachian Studies. 2023/04, Vol. 29, Issue 1, p47
  • Document Type:Article
  • Subject Area:History
  • Publication Date:2023
  • ISSN:1082-7161
  • DOI:10.5406/23288612.29.1.04
  • Accession Number:164720256
  • Copyright Statement:Copyright of Journal of Appalachian Studies is the property of Appalachian Studies Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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