How do considerations related to backlash affect the desirability of pursuing otherwise justified immigration policies? This paper argues that backlash-related considerations bear on immigration policy decisions in ways that are both more powerful and complicated than typically recognized. The standard possibility, the egalitarian backlash argument, endorses immigration restrictions in order to protect support for egalitarian distributive institutions. The paper shows that this account does not, by itself, provide a convincing rationale for restricting immigration because such diminished support is (a) likely outweighed by the benefits of more permissive immigration policies and (b) caused by the objectionable preferences of citizens. However, the paper develops an alternative account of the relevance of backlash-related considerations, the democratic backlash argument, which holds that increased levels of immigration threaten to contribute to undermining democratic institutions. This argument provides a more powerful rationale for restricting immigration, one that can—under identified conditions—justify immigration restrictions.

We show, against skeptics, that however latent it may be in everyday life, the ability to reason effectively about politics can readily be activated when conditions are right. We justify a definition of deliberative reason, then develop and apply a Deliberative Reason Index (DRI) to analysis of 19 deliberative forums. DRI increases over the course of deliberation in the vast majority of cases, but the extent of this increase depends upon enabling conditions. Group building that activates deliberative norms makes the biggest difference, particularly in enabling participants to cope with complexity. Without group building, complexity becomes more difficult to surmount, and planned direct impact on policy decisions may actually impede reasoning where complexity is high. Our findings have implications beyond forum design for the staging of political discourse in the wider public sphere.

Political candidates use Spanish-language appeals in efforts to increase their support among Hispanic voters. We argue that candidates, Hispanic or not, can use Spanish to signal closeness to Hispanics and posit that the effectiveness of these appeals is conditional on proficiency. To test this, we run two experiments where participants listen to an audio clip of a hypothetical candidate’s stump speech. We vary the ethnicity of the candidate (Anglo or Hispanic) and the language of the speech (English, non-native Spanish, and native-like Spanish). We find that Hispanic support for the Anglo and Hispanic candidates is higher in the native-like Spanish condition compared with the English-only condition. Relative to the English condition, non-native Spanish does not increase support for the Anglo candidate, but it decreases support for the Hispanic candidate. We find mixed effects for Anglo participants. Our results suggest that candidates can effectively appeal to Hispanic voters using Spanish-language messages.

Despite substantial research on descriptive representation for Blacks and Latinos, we know little about the electoral conditions under which Asian candidates win office. Leveraging a new dataset on Asian American legislators elected from 2011 to 2020, combined with pre-existing and newly conducted surveys, we develop and test hypotheses related to Asian American candidates’ ingroup support, and their crossover appeal to other racial and ethnic groups. The data show Asian Americans preferring candidates of their own ethnic origin and of other Asian ethnicities to non-Asian candidates, indicating strong ethnic and panethnic motives. Asian candidates have comparatively strong crossover appeal, winning at higher rates than Blacks or Latinos for any given percentage of the reference group. All else equal, Asian American candidates fare best in multiracial districts, so growing diversity should benefit their electoral prospects. This crossover appeal is not closely tied to motives related to relative group status or threat.

Since 2010, independent expenditures have grown as a source of spending in American elections. A large and growing portion comes from “dark money” groups—political nonprofits whose terms of incorporation allow them to partially obscure their sources of income. I develop a new dataset of about 2,350,000 tax documents released by the IRS and use it to test a new theory of political spending. I posit that pathways for anonymous giving allowed interest groups to form new networks and create new pathways for money into candidate races apart from established political parties. Akin to networked party organizations discovered by other scholars, these dark money networks channel money from central hubs to peripheral electioneering groups. I further show that accounting for these dark money networks makes previously peripheral nodes more important to the larger network and diminishes the primacy of party affiliated organizations in funneling money into candidate races.

Crises and disasters give voters an opportunity to observe the incumbent’s response and reward or punish them for successes and failures. Yet, even when voters perceive events similarly, they tend to attribute responsibility selectively, disproportionately crediting their party for positive developments and blaming opponents for negative developments. We examine selective attribution during the COVID-19 pandemic in the United States, reporting three key findings. First, selective attribution rapidly emerged during the first weeks of the pandemic, a time in which Democrats and Republicans were otherwise updating their perceptions and behavior in parallel. Second, selective attribution is caused by individual-level changes in perceptions of the pandemic. Third, existing research has been too quick to explain selective attribution in terms of partisan-motivated reasoning. We find stronger evidence for an explanation rooted in beliefs about presidential competence. This recasts selective attribution’s implications for democratic accountability.

In this paper, we explain how presidents strategically invest in administrative capacity, noting that presidents have few incentives to invest effort in capacity building in most agencies. We test our account with two analyses. First, we examine the time it took for the Bush, Obama, Trump, and Biden Administrations to nominate individuals to appointed positions. We find that presidents prioritize appointments to policy over management positions and that nominations occur sooner in agencies that implement presidential priorities. Second, we examine the responses of federal executives to the 2020 Survey on the Future of Government Service to see whether perceptions of presidential investment in administrative capacity match our predictions. We find that federal executives perceive higher levels of investment when the agency is a priority of the president and when the agency shares the president’s policy views. We conclude with implications for our understanding of the modern presidency and government performance.

Recently, we have witnessed the politicizing effects of police killings in the United States. This project asks how such killings might (de)mobilize voters at the local level. We draw on multiple theoretical approaches to develop a theory of community contact with the police. We argue that when a highly visible event tied to government actions occurs—like a police killing—it can spur turnout. This is especially true where public narratives tie such events to government and structural causes. By comparing neighborhoods near a killing before and after election day, we estimate the causal effect on turnout. We find a mobilizing effect. These effects are larger when they “trend” on Google, occur in Black communities, or if the victim is Black. Proximity to a killing also increases support for abolishing the police. We conclude that police violence increases electoral participation in communities where narratives about racially unjust policing resonate most.

How do government counterinsurgency tactics shape the behavior of the rebels they are combating? This letter builds upon foundational theories of civil war to argue that within-conflict government actions can further increase rebels’ levels of grievances. This increases the likelihood rebels continue fighting as conflicts unfold. I test the argument using newly compiled individual-level data on over 1,700 members of the Irish Volunteers and Irish Citizen Army who participated in the 1916 Easter Rising. Rebels varied in whether they were interned after the uprising. I show that rebels who were interned were more likely to fight throughout the entire Irish War of Independence. Qualitative evidence corroborates the contention that internment increased rebels’ levels of grievances. The letter elucidates how within-conflict events shape rebel behavior, by documenting how the tactics governments employ as they fight can shape the subsequent actions of the rebels they are combating.

Who gets to “speak up” in politics? Whose voices are silenced? We conducted two field experiments to understand how harassment shapes the everyday experiences of politics for men and women in the United States today. We randomized the names campaign volunteers used to text supporters reminders to participate in a protest and call their representatives. We find that female-named volunteers receive more offensive, silencing, and withdrawal responses than male-named or ambiguously named volunteers. However, supporters were also more likely to respond and agree to their asks. These findings help make sense of prior research that finds women are less likely than men to participate in politics, and raise new questions about whether individual women may be perceived as symbolic representatives of women as a group. We conclude by discussing the implications for gender equality and political activism.

Research shows that sexist attitudes are deeply ingrained, with adverse consequences in the socioeconomic and political sphere. We argue that parental leave for fathers—a policy reform that disrupts traditional gender roles and promotes less stereotypical ones—has the power to decrease attitudinal gender bias. Contrasting the attitudes of new parents who were (and were not) directly affected by a real-world policy reform that tripled the amount of fathers’ leave, we provide causal evidence that the reform increased gender-egalitarian views in the socioeconomic and political domains among mothers and fathers, and raised support for pro-female policies that potentially displace men among mothers. In contrast, informational, indirect exposure to the reform among the general public produced no attitudinal change. These results show that direct exposure to progressive social policy can weaken sexist attitudes, providing governments with a practical and effective tool to reduce harmful biases.

How does the gender composition of deliberative committees affect citizens’ evaluations of their decision-making processes? Do citizens perceive decisions made by gender-balanced, legislative bodies as more legitimate than those made by all-male bodies? Extant work on the link between women’s descriptive representation and perceptions of democratic legitimacy in advanced democracies finds the equal presence of women legitimizes decision-making. However, this relationship has not been tested in more patriarchal, less democratic settings. We employ survey experiments in Jordan, Morocco, and Tunisia to investigate how citizens respond to gender representation in committees. We find that women’s presence promotes citizens’ perceptions of the legitimacy of committee processes and outcomes and, moreover, that pro-women decisions are associated with higher levels of perceived legitimacy. Thus, this study demonstrates the robustness of findings from the West regarding gender representation and contributes to the burgeoning literature on women and politics.

When choosing what cases to investigate, do the police discriminate on the basis of caste and class? We employ a conjoint design to evaluate biases in police officers’ preferences for investigation based on perpetrator attributes. Conducting a survey of law enforcement officers in Nepal, we find evidence of discriminatory investigation practices. Absent constraining protocols that reduce officer discretion, police officers are more likely to target offenders who are from caste-class subjugated communities. Additionally, police officers’ assessments of institutional investigatory preferences reveal caste-based considerations: officers believe the police, in general, prefer to investigate low-caste offenders over high-caste offenders. They do not, however, perceive their institution as having class-based biases. These findings add to the body of evidence on whether police discriminate, which has previously focused on use of lethal force and police stops, and further demonstrate that concerns over systemic bias in policing are warranted.

Do democratic regimes depend on public support to avoid backsliding? Does public support, in turn, respond thermostatically to changes in democracy? Two prominent recent studies (Claassen 2020a; 2020b) reinvigorated the classic hypothesis on the positive relationship between public support for democracy and regime survival—and challenged its reciprocal counterpart—by using a latent variable approach to measure mass democratic support from cross-national survey data. However, both studies used only the point estimates of democratic support. We show that incorporating the concomitant measurement uncertainty into these analyses reveals that there is no support for either study’s conclusion. Efforts to minimize the uncertainty by incorporating additional survey data still fail to yield evidence in support of either hypothesis. These results underscore the need for both more nuanced analyses of the relationships between public support and democracy and taking measurement uncertainty into account when working with latent variables.

A wealth of recent research in comparative politics examines how spatial variation in historical conditions shapes modern political outcomes. In an article in the American Political Science Review, Homola, Pereira, and Tavits argue that Germans who live nearer to former Nazi concentration camps are more likely to display out-group intolerance. Clarifying the conceptual foundations of posttreatment bias and reviewing the historical record on postwar state creation in Germany, we argue that state-level differences confound the relationship between distance to camps and out-group intolerance. Using publicly available European Values Survey data and electoral results from 2017, we find no consistent evidence that distance to camps is related to contemporary values. Our findings have implications for literatures on historical persistence, causal inference with spatial data, Holocaust studies, and outgroup tolerance.

Multilevel regression and post-stratification (MRP) is a popular use of hierarchical models in political science. Multiple papers have suggested that relying on machine learning methods can provide substantially better performance than traditional approaches that use hierarchical models. However, these comparisons are often unfair to traditional techniques as they omit possibly important interactions or nonlinear effects. I show that complex (“deep”) hierarchical models that include interactions can nearly match or outperform state-of-the-art machine learning methods. Combining multiple models into an ensemble can improve performance, although deep hierarchical models are themselves given considerable weight in these ensembles. The main limitation to using deep hierarchical models is speed. This paper derives new techniques to further accelerate estimation using variational approximations. I provide software that uses weakly informative priors and can estimate nonlinear effects using splines. This allows flexible and complex hierarchical models to be fit as quickly as many comparable machine learning techniques.

Pepinsky, Goodman, and Ziller (2024, American Political Science Review, PGZ) reassess a recent study on the long-term consequences of concentration camps in Germany. The authors conclude that accounting for contemporary (i.e., post-treatment) state heterogeneity in the models provides unbiased estimates of the effects of camps on current-day outgroup intolerance. In this note, we show that PGZ’s empirical strategy rests on (a) a mischaracterization of what regional fixed effects capture and (b) two unrealistic assumptions that can be avoided with pre-treatment state fixed effects. We further demonstrate that results from the original article remain substantively the same when we incorporate regional fixed effects correctly. Finally, simulations reveal that camp proximity consistently outperforms spatially correlated noise in this specific study. The note contributes to the growing literature on legacy studies by advancing the discussion about the correct modeling choices in this challenging field.