Are policy arguments more or less persuasive when they are made by female politicians? Using a diverse sample of American respondents, we conduct a survey experiment which randomly varies the gender associated with two co-partisan candidates across four policy debates. We find strong effects contingent on respondent partisanship and gender, most notably on the issue of access to birth control. On this issue, regardless of the candidate's stance, Democratic respondents, particularly Democratic men, are much more likely to agree with the female candidate. Conversely, Republican respondents, particularly Republican women, are much more likely to agree with the male candidate. We discuss the implications of our findings for the meaning of gender as a heuristic in a highly partisan environment.

When the United States intervenes in foreign countries, the lives of both foreign combatants and foreign civilians are put at risk. I examine two rhetorical strategies, the use of sanitized and dehumanizing language that can influence the public's support of foreign intervention. In the context of foreign policy, sanitized language operates by obscuring casualties of war, while dehumanizing language operates by devaluing the lives of groups of individuals. Drawing on data from two experiments, I find that sanitized language operates through creating less of an emotional reaction toward casualties of war, which causes individuals to adopt more hawkish foreign policy attitudes. I find that dehumanizing language also leads to more hawkish foreign policy attitudes, but, contrary to expectations, does not lead to increased disgust or anger toward dehumanized groups.

What is the effect of violence on political mobilization? Taking the repression-mobilization nexus debate as a starting point, we study the effects of police interventions on political participation, focusing on the Spanish police crackdown on Catalonia's independence referendum on 1 October 2017. We analyze the effect of police actions on turnout using detailed aggregate data, as well as a survey conducted a few days after the referendum. The two empirical approaches show that police interventions had both deterrent and inverse spatial spillover effects. Although police raids had a local negative impact on turnout, they induced positive spillover effects in the surrounding areas. Our findings also indicate heterogeneity in the spatial dynamics, with police actions encouraging people to go to vote in nearby areas, but also mobilizing residents in neighboring areas to participate, especially those individuals with fewer incentives to turn out to vote.

When separation is a problem in binary dependent variable models, many researchers use Firth's penalized maximum likelihood in order to obtain finite estimates (Firth, 1993; Zorn, 2005; Rainey, 2016). In this paper, I show that this approach can lead to inferences in the opposite direction of the separation when the number of observations are sufficiently large and both the dependent and independent variables are rare events. As large datasets with rare events are frequently used in political science, such as dyadic data measuring interstate relations, a lack of awareness of this problem may lead to inferential issues. Simulations and an empirical illustration show that the use of independent “weakly-informative” prior distributions centered at zero, for example, the Cauchy prior suggested by Gelman et al. (2008), can avoid this issue. More generally, the results caution researchers to be aware of how the choice of prior interacts with the structure of their data, when estimating models in the presence of separation.

Focusing on one specific aspect of immigrant political integration—how authorities deal with their political right to demonstrate—we show in a large-scale survey experiment that liberal policy decisions permitting demonstrations lead to a polarization in attitudes: citizens who agree with a permission become more sympathetic, while those in favor of banning become more critical of immigrants. This notion of opinion backlash to policy decisions adds a new perspective to the literature on immigration attitudes which has either assumed a congruence between public opinion and policy or ignored political sources of anti-immigrant sentiment altogether. By exploring the unintended consequences of policy decisions, we provide an alternative view and demonstrate the inherent dilemma of balancing citizen opinion and minority rights.

Electoral violence is conceived of as violence that occurs contemporaneously with elections, and as violence that would not have occurred in the absence of an election. While measuring the temporal aspect of this phenomenon is straightforward, measuring whether occurrences of violence are truly related to elections is more difficult. Using machine learning, we measure electoral violence across three elections using disaggregated reporting in social media. We demonstrate that our methodology is more than 30 percent more accurate in measuring electoral violence than previously utilized models. Additionally, we show that our measures of electoral violence conform to theoretical expectations of this conflict more so than those that exist in event datasets commonly utilized to measure electoral violence including ACLED, ICEWS, and SCAD. Finally, we demonstrate the validity of our data by developing a qualitative coding ontology.

People are commonly expected not to waste their vote on parties with small probabilities of being elected. Yet, many end up voting for underdogs. We argue that voters gauge the popular support for their preferred party from their social networks. When social networks function as echo chambers, a feature observed in real-life networks, voters overestimate underdogs’ chances of winning. We conduct voting experiments in which some treatment groups receive signals from a simulated network. We compare the effect of networks with a high degree of homogeneity against random networks. We find that homophilic networks increase the level of support for underdogs, which provides evidence to back up anecdotal claims that echo chambers foster the development of fringe parties.

Models testing interactive and quadratic hypotheses are common in Political Science but control strategies for these models have received little attention. Common practice is to simply include additive control variables, without relevant product terms, into models with interaction or quadratic terms. In this paper, we show in Monte Carlos that interaction terms can absorb the effects of other un-modeled interaction and non-linear effects and analogously, that included quadratic terms can reflect omitted interactions and non-linearities. This problem even occurs when included and omitted product terms do not share any constitutive terms. We show with Monte Carlo experiments that regularized estimators, the adaptive Lasso, Kernel Regularized Least Squares (KRLS), and Bayesian Additive Regression Trees (BART) can prevent the misattribution of interactive/quadratic effects, minimize the problems of efficiency loss and overfitting, and have low false-positive rates. We illustrate how inferences drawn can change when relevant product terms are used in the control strategy using a recent paper. Implementing the recommendations of this paper would increase the reliability of conditional and non-linear relationships estimated in many papers in the literature.

Where do armed conflicts occur? In applied studies, we may take ad hoc approaches to answer this question. In some regression studies, for instance, a single conflict event can cause an entire province to be classified as a conflict zone. In this paper, I fill this void of knowledge by developing a machine learning method that is less dependent on the areal-unit assumptions and can flexibly estimate conflict zones. I apply the method to a conflict event dataset and create a new dataset of conflict zones. A replication of Daskin and Pringle (2018, Nature 553, 328–332) with the new dataset indicates that the effect of civil war on mammal populations is much smaller than the original estimate.

Amazon's Mechanical Turk is widely used for data collection; however, data quality may be declining due to the use of virtual private servers to fraudulently gain access to studies. Unfortunately, we know little about the scale and consequence of this fraud, and tools for social scientists to detect and prevent this fraud are underdeveloped. We first analyze 38 studies and show that this fraud is not new, but has increased recently. We then show that these fraudulent respondents provide particularly low-quality data and can weaken treatment effects. Finally, we provide two solutions: an easy-to-use application for identifying fraud in the existing datasets and a method for blocking fraudulent respondents in Qualtrics surveys.

Ethnic relations play an important political role in many countries and can have serious consequences for policy and stability, with many conflicts occurring along ethnic lines. While most studies on ethnic relations focus on the behavior of the general public, ethnic bias among political elites may be equally consequential but remains understudied. This study explores tools that improve interethnic cooperation among politicians in governance (rather than electoral competition). We argue that shared interests incentivize elites to overcome ethnic bias. We conduct two experiments (one survey and one lab-in-the-field) with local politicians in Bosnia and Herzegovina and find support for this expectation, i.e., concrete information about shared policy priorities and goals foster interethnic cooperation.

We explore mediated representations of parties' campaign interactions in multi-party systems. Actors in multi-party systems can engage with different actors on multiple issues. One crucial aspect of such engagement is the element of negativity—voicing criticisms of other actors' actions and policy proposals. This contribution argues that the media systematically exaggerate patterns of negativity based on issue ownership structures, such that attacks originating from or targeting issue owners are significantly more likely to be covered. We analyze a broad sample of news content from the 2013 Austrian national election campaign with generalized exponential random graph models to capture the complexities of mediated campaign negativity in a multi-party system while controlling for non-mediated campaign negativity. The results show that issue owners are more likely to be featured as attackers and targets in owned policy domains, suggesting a violation of the normative ideal of a fair representation of campaign interactions.

In comparative studies, causal evaluations attempt to improve our understanding of the effectiveness of structural reforms by counterfactually inspecting post-treatment effects. Yet, even if comparative scholars find similar treatment and comparison units, the interpretation of the post-treatment trajectory is difficult as short-term estimates can be subject to strategic timing of reform implementation, while long-term effects are likely affected by further interventions. To illustrate these difficulties we apply the generalized synthetic control method to evaluate the introduction of a British national minimum wage. We find a short-term decreasing effect on youth unemployment that turns into an increasing effect over time. This suggests the presence of an upward biased selection effect from strategic timing. We also inspect two post-treatment interventions and find that they differ in their general and country-specific implications for the long-term trajectory.

Despite its many contributions, a central problem in the dualization debate is conceptual overstretching, as we will argue in this short comment. The term “dualization” has been used to describe different processes, which are often subsumed under this heading: the rise of atypical employment, increasing labor market stratification in general, or the partial deregulation of welfare state policies and institutions. This multitude of usages weakens the utility of dualization as a theoretical concept. In the next section, we briefly look at the evolution of the dualization debate on the micro level before we proceed to the macro level. In the concluding section, we speculate about the future of dualization as a concept for describing welfare state transformations.

In the context of recent economic and financial crisis in Europe, questions about the power of the core executive to control fiscal outcomes are more important than ever. Why are some governments more effective in controlling spending while others fall prey to excessive overspending by individual cabinet ministers? We approach this question by lifting the veil of collective cabinet responsibility and focusing on intra-cabinet decision-making around budgetary allocation. Using the contributions of individual cabinet members during budget debates in Ireland, we estimate their positions on a latent dimension that represents their relative levels of support or opposition to the cabinet leadership. We find some evidence that ministers who are close to the finance minister receive a larger budget share, but under worsening macro-economic conditions closeness to the prime minister is a better predictor for budget allocations. Our results highlight potential fragility of the fiscal authority delegation mechanism in adverse economic environment.

What attracts voters to far-right parties? Emphasizing the repercussions of far-right parties' past achievements on the mobilization of voters' electoral demand, this paper develops an argument of context-dependent strategic far-right voting. Far-right parties seek to mobilize on a combination of demand for nativist policies and anti-establishment protest sentiment. Their capacity of doing so, however, critically depends on the strategic incentives they supply. My findings from a comparative analysis based on six waves of the European Election Study show that far-right parties' past attainment of legislative strength boosts the credibility of their policy appeal and broadens the scope of their protest appeal whereas their participation in government jeopardizes their capacity to mobilize on popular discontent.

This study analyzes how migrants affect their host country's foreign policy toward their home country by measuring their influence on bilateral emergency aid. I develop the argument that besides political lobbying and the targeting of aid by the donor country, migrants affect emergency aid by providing a linkage between the countries and increasing the salience of a disaster abroad. The empirical analysis shows that the location and size of a country's diaspora is an important predictor of emergency aid flows after natural disasters. Interaction effects provide support for the linkage argument: while the diaspora effect does not increase with the host country's level of democracy, it is strongest with the least severe and most distant disasters.

Mixed-methods designs, especially those in which case selection is regression-based, have become popular across the social sciences. In this paper, we highlight why tools from spatial analysis—which have largely been overlooked in the mixed-methods literature—can be used for case selection and be particularly fruitful for theory development. We discuss two tools for integrating quantitative and qualitative analysis: (1) spatial autocorrelation in the outcome of interest; and (2) spatial autocorrelation in the residuals of a regression model. The case selection strategies presented here enable scholars to systematically use geography to learn more about their data and select cases that help identify scope conditions, evaluate the appropriate unit or level of analysis, examine causal mechanisms, and uncover previously omitted variables.

The political relevance of labor market insecurity has been questioned because (a) insider-outsider divides were considered to be a divide within the low-skilled and politically less active working class and (b) labor market insecurity runs through the middle of the household. Outsiders might therefore align their preferences with those of insiders. This contribution provides, first, evidence that labor market insecurity extends well into the higher-skilled middle class, in particular to high-skilled young adults and high-skilled women. Second, the contribution sheds light on the “household question”, that is the question whether mixed households dampen the political relevance of labor market insecurity. If labor market insecurity is concentrated in specific social groups (young adults, women) that tend to cohabit with secure insiders, the political relevance of labor market insecurity might depend on whether or not outsiders align their preferences with those of the household. In this contribution, I discuss recent work on the relevance of the household in translating labor market divides into preferences divides presenting recent work that shows that the household does not render insider-outsider divides politically irrelevant. In sum, insider-outsider divides have all the potential to become politically relevant.

The Transatlantic Trade and Investment Partnership between the European Union and the US is highly technical. Still, the negotiations triggered large-scale protests among citizens with very diverse socioeconomic backgrounds. Why has a complex issue such an enormous mobilizing effect although the economic consequences are either unclear or favorable for the participating economies? We argue that the transparency of negotiations is an important consideration for people evaluating the negotiation outcome. Conducting a survey experiment, we show that non-transparent decision-making decreases citizens' appraisal of the agreement independent of its outcome: A non-transparent negotiation is, on average, almost 16 percent less likely to find public approval than a transparent but otherwise identical agreement. Our findings have important implications for democratic decision-making.