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Social well-being in the Appalachian coalfields

  • Year: 2010
  • Author: Woods, Bradley R.
  • Journal Name: ProQuest Dissertations and Theses
  • Publisher: The Pennsylvania State University
  • Published Location: United States -- Pennsylvania
  • ISBN: 9781124163451
  • Country: United States
  • State/Region: Appalachia

Growing energy demands have shifted production styles and approaches associated with traditional fuel sources, including coal. This project focused on a new and increasingly contested method of coal extraction, Mountaintop Removal coal mining (MTR) and its effects on the social well-being of central Appalachian coalfield communities vis-à-vis their socioeconomic and biophysical vulnerability. Attention is given to this region because their coalfields have undergone major changes as a result of two interrelated forces: (1) a national push for energy independence that led to the region's all-time high production of coal (supplying over half of the nation's coal); and (2) changes in mining technology that allowed for increased production with reduced labor. While most policymakers are aware of the negative environmental effects of MTR, its continued use is rationalized with the argument that it contributes to local economies.

This comparative study was designed to examine the role of MTR coal mining and its impact on social well-being. Through the analysis of secondary data, extensive key informant interviews, and analysis of household survey data, social well-being in central Appalachian mining-dependent communities was evaluated.

Findings from this research indicated biophysical vulnerability, specifically problems with coal mining, was the greatest predictor of social well-being. Other significant factors of social well-being were household income, community satisfaction, and community events. Additionally, there were important differences between respondents in MTR versus non-MTR communities. However, regression models for each community indicated the problems experienced with coal mining was the most important variable in predicting social well-being in both communities. Implications for applied policy are presented.

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