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Journal ArticleDOI

Politicized Places: Explaining Where and When Immigrants Provoke Local Opposition

Daniel J. Hopkins
- 01 Feb 2010 - 
- Vol. 104, Iss: 01, pp 40-60
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TLDR
This article developed the politicized places hypothesis, an alternative that focuses on how national and local conditions interact to construe immigrants as threatening, and tested the hypothesis using new data on local anti-immigrant policies.
Abstract
In ethnic and racial terms, America is growing rapidly more diverse. Yet attempts to extend racial threat hypotheses to today's immigrants have generated inconsistent results. This article develops the politicized places hypothesis, an alternative that focuses on how national and local conditions interact to construe immigrants as threatening. Hostile political reactions to neighboring immigrants are most likely when communities undergo sudden influxes of immigrants and when salient national rhetoric reinforces the threat. Data from several sources, including twelve geocoded surveys from 1992 to 2009, provide consistent support for this approach. Time-series cross-sectional and panel data allow the analysis to exploit exogenous shifts in salient national issues such as the September 11 attacks, reducing the problem of residential self-selection and other threats to validity. The article also tests the hypothesis using new data on local anti-immigrant policies. By highlighting the interaction of local and national conditions, the politicized places hypothesis can explain both individual attitudes and local political outcomes.

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Citations
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Journal ArticleDOI

Estimating anti-immigrant sentiment for the American states using multi-level modeling and post-stratification, 2004–2008:

TL;DR: This article used survey aggregation with multilevel regression and post-stratification (MRP) for the period 2004 to 2008 to estimate anti-immigrant sentiment at the state level.
Book ChapterDOI

Moving to diversity: residential mobility, changes in ethnic diversity, and concerns about immigration

TL;DR: In this article, the authors show that individuals who move to a more diverse neighborhood are about 13% more likely to become very concerned about immigration and this effect remains even three years after the move.
Journal ArticleDOI

Local Immigration Enforcement and Local Economies

TL;DR: This article examined the impacts of a locally enforced immigration program on private employer reports to the Quarterly Census of Employment and Wages and identified impacts on immigrant-intensive industries that are robust to prepolicy time trends, implementation timing, and the exclusion of pairs with large prepolicy differences.
Journal ArticleDOI

The Spatiality of Local Immigration Policies in the United States

TL;DR: The authors argue that spatial relationships like scale, networks, and place, which tend to be treated as ontologically separate, ought to be considered as mutually constitutive, and argue that this framework helps explain why local communities have pursued vastly different policy responses to immigration in the United States.
Journal ArticleDOI

Explaining immigration preferences: Disentangling skill and prevalence:

TL;DR: One of the most important and consistent findings to emerge from the study of immigration politics over the past decade is the seemingly uniform preference among mass citizenries for high-skilled immigrants.
References
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Book ChapterDOI

Prospect theory: an analysis of decision under risk

TL;DR: In this paper, the authors present a critique of expected utility theory as a descriptive model of decision making under risk, and develop an alternative model, called prospect theory, in which value is assigned to gains and losses rather than to final assets and in which probabilities are replaced by decision weights.
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Data Analysis Using Regression and Multilevel/Hierarchical Models

TL;DR: Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models.
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Mostly Harmless Econometrics: An Empiricist's Companion

TL;DR: The core methods in today's econometric toolkit are linear regression for statistical control, instrumental variables methods for the analysis of natural experiments, and differences-in-differences methods that exploit policy changes.
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Analysis of Incomplete Multivariate Data

TL;DR: The Normal Model Methods for Categorical Data Loglinear Models Methods for Mixed Data and Inference by Data Augmentation Methods for Normal Data provide insights into the construction of categorical and mixed data models.
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