This study develops a new theoretical approach and empirical measure of American regional subcultures using public opinion survey data and building on previous research (Chinni and Gimpel 2011; Elazar 1962, 1966; Hero 2000; Lieske 1993; Putnam, Leonardi and Nanetti 1994). Instead of approaching classification of regions based on formal geography, border states, population demography, ethnic groups and migration patterns, or historical traditions, this study uses a vernacular geography approach to study culture in the 50 American states. Vernacular geography is the sense of place revealed in ordinary people’s language. The study uses original nationwide survey data to measure perceptions of place based on states that are most similar to a respondent’s home state. The measure is based on unique survey questions where respondents have the freedom to choose any of the 50 states. The surveys are conducted by the Cooperative Congressional Election Study (CCES) from 2012 to 2016. These data allow development of a new measure of state similarity or regional subcultures based on vernacular geography. The state similarity network based on people’s feelings shows that state contiguity is not the driving factor in people’s perceptions of regions of the United States. It also shows that people’s perceptions of state similarity are a better predictor of policy diffusion than contiguity. Finally, this study shows that wealth is the most important factor in people’s perceptions of state similarity, but that population size, racial diversity, rural/urban population density, and ideology/partisanship are all predictors of people’s perceptions of state similarity at low levels. This study argues that perceptions of place matter. They are a core building block of political culture and are important for understanding policy diffusion. This study is about how citizens conceptualize their home state and network of most similar states, and whether state similarity networks, or social networks of states, influence government policy adoption and innovation.
| Identifer | oai:union.ndltd.org:uiowa.edu/oai:ir.uiowa.edu:etd-7875 |
| Date | 01 August 2018 |
| Creators | Bricker, Christine |
| Contributors | Tolbert, Caroline J. |
| Publisher | University of Iowa |
| Source Sets | University of Iowa |
| Language | English |
| Detected Language | English |
| Type | dissertation |
| Format | application/pdf |
| Source | Theses and Dissertations |
| Rights | Copyright © 2018 Christine Bricker |
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