Abstract: The theorization and empirical exploration of contextual effects is a long-standing feature of public opinion and political behavior research. At present, however, there is little to no evidence that citizens actually perceive the local contextual factors theorized to influence their attitudes and behaviors. In this article, we focus on two of the most prevalent contextual factors appearing in theories—racial/ethnic and economic context—to investigate whether citizens’ perceptions of their local ethnic and economic contexts map onto variation in the actual ethnic composition and economic health of these environments. Using national survey data combined with Census data, and focusing on the popular topics of immigration and unemployment, we find that objective measures of the size of the immigrant population and unemployment rate in respondents’ county and zip code strongly predict perceived levels of local immigration and assessments of the health of one’s local job market. In addition to demonstrating that citizens are “receiving the treatment,” we show that perceptions of one’s context overwhelmingly mediate the effect of these objective contextual factors on relevant economic and immigration attitudes. The results from our analyses provide scholars with unprecedented evidence that a key perceptual process presumed in various contextual theories of political attitudes and behavior is, in fact, valid.
Abstract: Immigrant populations in many developed democracies have grown rapidly, and so too has an extensive literature on natives' attitudes toward immigration. This research has developed from two theoretical foundations, one grounded in political economy, the other in political psychology. These two literatures have developed largely in isolation from one another, yet the conclusions that emerge from each are strikingly similar. Consistently, immigration attitudes show little evidence of being strongly correlated with personal economic circumstances. Instead, research finds that immigration attitudes are shaped by sociotropic concerns about its cultural impacts—and to a lesser extent its economic impacts—on the nation as a whole. This pattern of results has held up as scholars have increasingly turned to experimental tests, and it holds for the United States, Canada, and Western Europe. Still, more work is needed to strengthen the causal identification of sociotropic concerns and to isolate precisely how, when,...
Abstract: Economic and cultural factors are often presented as alternative explanations of Brexit. Most studies have failed to recognize the interplay between contextual economic factors and individual attit...
Abstract: Direct democracy plays a prominent role in the explanation of institutional trust. To date, however, empirical findings on the effects of direct democracy remain inconclusive. In this article, we argue that this inconclusiveness can be partly ascribed to the diverse effects direct democracy has on individuals. In other words, direct democracy influences institutional trust, but how and to what degree depends on individuals’ personality traits. Running hierarchical analyses of unique survey data from a random sample of eligible Swiss voters, we document three findings: First, we show that the number of ballot measures is not directly associated with institutional trust. Second, we demonstrate that the Big Five personality traits affect the propensity to trust. Third, some of these traits also alter the relationship between direct democracy and institutional trust, suggesting that certain personality types are more likely to be sensitive to popular votes than others and that not everyone is equally likely to respond to political stimuli, even in highly democratic environments.
Cites background from "Are Citizens "Receiving the Treatme..."
...In line with key insights of psychology we thus maintain that the effect of a situation (here direct democratic context) depends on the person who apprehends it (Funder 2008, 571; Newman et al. 2013, 8; Sherman et al. 2013, 11)....
Abstract: Existing research makes competing predictions and yields contradictory findings about the relationships between natives’ exposure to immigrants and their attitudes toward immigration. Engaging this disjuncture, this article argues that individual predispositions moderate the impact of exposure to immigrants on negative attitudes toward immigrants. Negative attitudes toward immigration are more likely among individuals who are most sensitive to such threats. Because country-level studies are generally unable to appropriately measure the immigration context in which individuals form their attitudes, this article uses a newly collected dataset on regional immigration patterns in Austria, Germany, and Switzerland to test the argument. The data show that increasing and visible diversity is associated with negative attitudes toward immigrants, but only among natives on the political right. This finding improves the understanding of attitudes toward immigrants and immigration and has implications for the study o...
TL;DR: This article offers an approach, built on the technique of statistical simulation, to extract the currently overlooked information from any statistical method and to interpret and present it in a reader-friendly manner.
Abstract: Social Scientists rarely take full advantage of the information available in their statistical results. As a consequence, they miss opportunities to present quantities that are of greatest substantive interest for their research and express the appropriate degree of certainty about these quantities. In this article, we offer an approach, built on the technique of statistical simulation, to extract the currently overlooked information from any statistical method and to interpret and present it in a reader-friendly manner. Using this technique requires some expertise, which we try to provide herein, but its application should make the results of quantitative articles more informative and transparent. To illustrate our recommendations, we replicate the results of several published works, showing in each case how the authors' own conclusions can be expressed more sharply and informatively, and, without changing any data or statistical assumptions, how our approach reveals important new information about the research questions at hand. We also offer very easy-to-use Clarify software that implements our suggestions.
Abstract: W e show that social scientists often do not take full advantage of the information available in their statistical results and thus miss opportunities to present quantities that could shed the greatest light on their research questions. In this article we suggest an approach, built on the technique of statistical simulation, to extract the currently overlooked information and present it in a reader-friendly manner. More specifically, we show how to convert the raw results of any statistical procedure into expressions that (1) convey numerically precise estimates of the quantities of greatest substantive interest, (2) include reasonable measures of uncertainty about those estimates, and (3) require little specialized knowledge to understand. The following simple statement satisfies our criteria: “Other things being equal, an additional year of education would increase your annual income by $1,500 on average, plus or minus about $500.” Any smart high school student would understand that sentence, no matter how sophisticated the statistical model and powerful the computers used to produce it. The sentence is substantively informative because it conveys a key quantity of interest in terms the reader wants to know. At the same time, the sentence indicates how uncertain the researcher is about the estimated quantity of interest. Inferences are never certain, so any honest presentation of statistical results must include some qualifier, such as “plus or minus $500” in the present example. Making the Most of Statistical Analyses: Improving Interpretation and Presentation
Abstract: More than thirty years after its original publication, V. O. Key's classic remains the most influential book on its subject. Its author, one of the nation's most astute observers, drew on more than five hundred interviews with Southerners to illuminate the political process in the South and in the nation.Key's book explains party alignments within states, internal factional competition, and the influence of the South upon Washington. It also probes the nature of the electorate, voting restrictions, and political operating procedures. This reprint of the original edition includes a new introduction by Alexander Heard and a profile of the author by William C. Havard. "A monumental accomplishment in the field of political investigation." Hodding Carter, New York Times "The raw truth of southern political behavior." C. Vann Woodward, Yale Review "[This book] should be on the 'must' list of any student of American politics." Ralph J. Bunche V.O. Key (1908-1963) taught political science at the University of California, Los Angeles, and at Johns Hopkins, Yale, and Harvard universities. He was president of the American Political Science Association and author of numerous books, including American State Politics: An Introduction (1956); Public Opinion and American Democracy (1961); and The Responsible Electorate (1966)."
Abstract: L'A. etudie la representation des prejudices. Il evalue la perception de la menace que les groupes subordonnes ferraient peser sur les groupes dominants. Il estime que les conditions economiques et l'importance des groupes subordonnes par rapport aux groupes dominants expliquent ce type de perception. Il note a partir de donneees europeennes des disparites entre les 12 sur ce plan precis. Cette perception de la menace « ethnique » expliquerait le sentiment de prejudice. L'A. invite aux vues de ses analyses a revoir celles du passe
Abstract: Preface to the Second Edition 1. Historical Foundations of Structural Equation Modeling for Continuous and Categorical Latent Variables 2. Path Analysis: Modeling Systems of Structural Equations Among Observed Variables 3. Factor Analysis 4. Structural Equation Models in Single and Multiple Groups 5. Statistical Assumptions Underlying Structural Equation Modeling 6. Evaluating and Modifying Structural Equation Models 7. Multilevel Structural Equation Modeling 8. Latent Growth Curve Modeling 9. Structural Models for Categorical and Continuous Latent Variables 10. Epilogue: Toward a New Approach to the Practice of Structural Equation Modeling