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Published in: Political Behavior 1/2023

18-02-2021 | Original Research

You’re Not From Here!: The Consequences of Urban and Rural Identities

Authors: Jeffrey Lyons, Stephen M. Utych

Published in: Political Behavior | Issue 1/2023

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Abstract

As the American political landscape becomes increasingly divided along urban–rural lines, it raises the prospect of deepening social identities that are tied to one’s community-type. As community-type becomes an important social identity, it can lead to favoritism of one’s community in-group, or denigration of one’s community out-group. We explore the extent to which urban and rural identities exist above and beyond other factors like party and race, and whether they are consequential for the ways in which people evaluate the political and non-political world. Using national survey data, we demonstrate that people in both urban and rural locations hold beliefs that are consistent with a community-type social identity that is independent of other factors which are correlated with the urban–rural divide. We use two different experiments to assess the consequences of this identity, finding that there are distinct effects in the political arena when allocating government resources, and in the non-political world when judging hypothetical job applications. These effects are generally smaller in magnitude than other factors, such as partisanship, but suggest that community-type identities are important in politics.

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Appendix
Available only for authorised users
Footnotes
1
We recognize that much research points to an urban–rural continuum being the better way to evaluate these matters (e.g. Scala and Johnson 2017) than a trichotomous conception of urban, suburban, and rural. While we do not disagree with this assessment, we are focused principally on the how these are manifested in the minds of voters, and given the prevalence of the terminology of urban, suburban, and rural, we believe that these are likely to be the most salient from an identity perspective.
 
2
A total of 5497 respondents we sampled for Wave 32. 4734 were respondents from the American Trends Panel, and 1517 were from GfK’s KnowledgePanel which was the rural oversample. Rural ZIP codes were defined as those that had fewer than 127 households per square mile. The survey was in the field from February 26th to March 11th, 2018. See https://​www.​pewsocialtrends.​org/​dataset/​american-trends-panel-wave-32/​ for more information on the survey, and to download the data.
 
3
In the full sample, 20.0% describe their community as being urban, 33.6% as rural, and 46.4% as suburban. This does represent an oversample of rural individuals, but the percent urban and suburban are not vastly different than what we might find in a representative sample. The American Housing Survey which is sponsored by HUD and conducted by the U.S. Census Bureau in 2017 finds that 52% of people describe their neighborhood as suburban, 27% as urban, and 21% as rural (HUD PD&R 2018). Using these numbers, we have an underrepresentation of urban respondents by 7%, and an underrepresentation of suburban respondents by 6%.
 
4
Age ranges from 1 to 4, with a mean of 2.8. Gender ranges from 1 to 2, where 1 is males and 2 is females, with 49.1% of the sample being male and 50.9% being female. Education ranges from 1 to 6, with a mean value of 4.0. Race is a dichotomous measure where 0 is white and 1 is non-white, 77.3% of the sample identifies as white and 22.7% identify as non-white. Income ranges from 1 to 9, with a mean of 5.8. Party ID ranges from 0 to 2, where 0 is Democrats, 1 is Independents, and 2 is Republicans. 37.3% of the sample identifies as Democrats, 30.6% as Independents, and 32.1% as Republicans. Ideology ranges from 1 to 5, where 1 is very liberal and 5 is very conservative, with a mean value of 3.1. Frequency of religious attendance ranges from 0 to 5, where 0 is never attend and 5 is attend more than once per week. The measure has a mean of 2.1.
 
5
Regression tables are available in the Appendix.
 
6
While it is beyond the scope of this paper to explore why all groups believe that rural communities receive less than their fair share, it is possible that media coverage of rural America that focuses on economic challenges and declining populations contribute to these perceptions.
 
7
Participants were required to be located in the United States and have a greater than 97% approval rating on all completed tasks.
 
8
The conjoint experiment was programmed in Qualtrics using Thomas Leeper’s invaluable publicly available example code: https://​github.​com/​leeper/​conjoint-example.
 
9
Full details of this conjoint design are available in the Appendix.
 
10
In all models, the bottom 5% of trials in terms of response timing are excluded. This excludes all trials where respondents read the information, and made the allocation decision, in less than 5.349 s. Results are substantively similar, though statistically less precise, when all respondents are included. Additionally, coefficients presented are from OLS models with standard errors clustered by respondent, with 90% confidence intervals indicated. Results are robust to logistic regression models, included in the Appendix.
 
11
We retain a total of 182 participants, and 5006 observations, for Urban respondents, and 91 participants, and 2,597 observations, for Rural respondents.
 
12
All results are robust to excluding participants from bad IP addresses, to address the potential for bad responses. We use the procedure from Kennedy et al. (2020) and Kennedy’s online application for checking IP addresses.
 
13
Because of ethical issues with unpaid screening on MTurk, and issues with participants potentially lying about their location in announced qualifications, we chose to pay suburban respondents who completed the study. Since we do not have clear predictions about how suburban respondents would respond to urban or rural individuals, they are excluded from all analyses.
 
14
We chose to not give pure partisan (with no location) cue treatments, as the effects of partisan discrimination in both political (see Mason 2018) and apolitical (Utych and Engelhardt 2020) settings are well documented.
 
15
Here, Ohio is selected as the location for all respondents. The state was kept constant to avoid cueing participants to partisanship in the non-partisan conditions (for example, comparing an urban person from New York City to a rural person from, say Texas, may cue partisan identity). Ohio is selected due to its relative status as a mixed partisan state, which we believe may minimize partisan cues. We do not expect that respondents are directly aware of Hillsboro, Ohio as a rural location, and rely on the other cues to signal this.
 
16
As such, all pure independents are excluded from analyses.
 
17
The rest selected that he was from a suburban area.
 
18
Results are relatively similar, but statistically less precise, when only urban or rural respondents are looked at. That is, the effect does not appear to be driven by only urban or rural respondents, but the estimates are less precise due to the smaller sample sizes. There is some suggestive evidence that, akin to study 2, rural respondents are exerting larger effects, and perhaps have a stronger location-based identity. Results are available in the Appendix.
 
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Metadata
Title
You’re Not From Here!: The Consequences of Urban and Rural Identities
Authors
Jeffrey Lyons
Stephen M. Utych
Publication date
18-02-2021
Publisher
Springer US
Published in
Political Behavior / Issue 1/2023
Print ISSN: 0190-9320
Electronic ISSN: 1573-6687
DOI
https://doi.org/10.1007/s11109-021-09680-3

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