Reacting to the Rural Burden: Understanding Opposition to Utility‐Scale Solar Development in Upstate New York.

  • Published In: Rural Sociology, 2023, v. 88, n. 2. P. 578 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Nilson, Roberta S.; Stedman, Richard C. 3 of 3

Abstract

Rural landscapes are under increasing development pressure from utility‐scale solar (USS) energy facilities while public attitudes toward these facilities remain poorly documented and understood. This study explores whether opposition to USS in upstate New York is shaped at least in part by perceived rural burden—the idea that rural people and places are unfairly expected to provide new renewable energy in response to urban demand. We explore the idea of rural burden with measures of distributive injustice, procedural injustice, periphery identity, and place attachment. We use a survey (N = 421) of residents of western and northern New York, regions with substantial new and pending USS development. We find that 42 percent of residents oppose USS installations in or near their local communities, 14 percent neither support nor oppose, and 44 percent support. Perceived distributive and procedural injustice, along with place attachment have the strongest effect on opposition, while socio‐demographic attributes, political ideology, and climate change beliefs were insignificant. These findings suggest that opposition to large scale renewable energy development exemplifies a rural environmental justice concern justified for many by the perceived legacy of exploitation in natural resource development. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Rural Sociology. 2023/06, Vol. 88, Issue 2, p578
  • Document Type:Article
  • Subject Area:Psychology
  • Publication Date:2023
  • ISSN:0036-0112
  • DOI:10.1111/ruso.12486
  • Accession Number:164307402
  • Copyright Statement:Copyright of Rural Sociology is the property of Wiley-Blackwell 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.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.