The primary purposes of this study were three-fold. First, the reputational methodology for studying community power structures was to be enhanced with computer assisted data analysis techniques to produce a tool that educational leaders could use in the quest for understanding the community power structure. Second, the method was to be altered to produce a tool for assessing the degree to which groups of educators understand the power structure. Third, the methodology was to be applied to a selected community in order to produce a model of the power structure that could be used to gauge the effectiveness of the methodology. The findings based on the data generated from the interviews with the influential people (influentials) revealed that the power structure in the selected community closely resembled the type that Kimbrough called "segmented pluralistic." No distinct power groups were revealed. The influentials apparently formed temporary alliances based on the issues. A ruling faction that always worked together to control decisions in the community did not emerge from the study. Educators ranked seven persons in the top ten identified by the influentials; however, educators tended to overlook the behind-the-scenes people identified by the influentials themselves. Educators agreed with influentials on the top two community issues; however, they tended to rank educational issues much higher than did the influentials. Strong agreement between the two groups was evident with regard to the influential organizations in the community. The variables used to characterize the influentials appeared to yield a distinct model of the community power structure. The methods used seem to be suitable for comparing the perceptions of educators with those of the influentials. Cluster analysis proved to be a useful technique for exploring relationships between variables and for discovering clusters in communication networks.
Identifer | oai:union.ndltd.org:ETSU/oai:dc.etsu.edu:etd-4017 |
Date | 01 May 1987 |
Creators | Allen, Charlie J. |
Publisher | Digital Commons @ East Tennessee State University |
Source Sets | East Tennessee State University |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Electronic Theses and Dissertations |
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