TRUMP, CHRISTIAN NATIONALISM, AND ISSUE POLARIZATION: THE ATTITUDES AND ACTIVISM OF IOWA CLERGY IN THE 2020 CAUCUSES

Prior research has investigated the differences between evangelical Protestant, mainline Protestant, and Catholic clergy in American general elections. We know less about attitudes and activism of clergy in presidential nomination campaigns. This research highlights results from a survey of 480 clergy on candidate support, issues, and political activism in the 2020 Iowa caucuses. A strong Iowa caucus showing often fuels momentum for candidates in the rest of the nomination race, as with Barack Obama in 2008. This 2020 survey covers issues such as immigration, racial justice, health care, and more. I also explore how Iowa clergy think about political activism and views on Christian nationalism. I find that most Democratic-leaning clergy supported center-left candidates in Iowa in 2020. Among Iowa clergy of all parties (including independents), most disapproved of the job Donald Trump was doing as President. A comparison with a 2012 survey reveals increasing polarization of the three clergy groups on political ideology, church-state issues, and racial justice.

Testing cognitive and interpersonal asymmetry vs. symmetry among voters in the 2020 Presidential primaries

During the 2020 U.S. Presidential primary season, we measured candidate support and cognitive and interpersonal variables associated with political ideology among 831 U.S. participants. Cognitive style variables included openness to experience, active open-minded thinking, dogmatism, and preference for one right answer. Interpersonal variables were compassion and empathy. We modeled candidate support across the political spectrum, ranging from the most conservative to the most liberal (Trump, Bloomberg, Biden, Warren, Sanders), testing competing pre-registered predictions informed by the symmetry and asymmetry perspectives on political ideology. Specifically, we tested whether mean levels on the variables of interest across candidate supporters conformed to patterns consistent with symmetry (i.e., a curvilinear pattern with supporters of relatively extreme candidates being similar to each other relative to supporters of moderate candidates) vs. asymmetry (e.g., linear differences across supporters of liberal vs. conservative candidates). Results broadly supported the asymmetry perspective: Supporters of liberal candidates were generally lower on cognitive rigidity and higher on interpersonal warmth than supporters of conservative candidates. Results and implications are discussed.

Place or Partisanship? The Conditional Role of Identities on Candidate Support

Recent work on the influence of social identities reveals that placed-based attachments serve as a powerful heuristic when making political assessments. When a politician makes a place-based appeal—such as cuing rural origins—individuals who share that identity more strongly support the candidate. Yet, other important identities—namely, partisanship—are strongly related to place. Here, we attempt to disentangle the unique influence of a place-based identity (and the strength thereof) on candidate support. Additionally, we ask whether shared place can compel supportive behavior, rather than merely increase expressive support. Using a unique survey experiment, we find that those who strongly identify with a place are more willing to donate to the campaign of a shared-place candidate, relative to weaker place identification, but only among co-partisans. We find little evidence that place attachment influences supportive behavior beyond the role of partisanship. Disparate identities—here, place and partisanship—that create cross-pressures can operate in tandem.

Correction to: Asian American Candidate Preferences: Evidence from California

Using the 2012–2018 California State Assembly races, Sadhwani finds that Asian Americans who live in places that are 15–30% have higher voter turnout. Turnout in these districts is also increased when an Asian candidate is on the ballot (2020). Although turnout is increased when an Asian American is on the ballot, it is unknown whether or not Asian voters also have a preference for candidates of the same race or candidates of the same national-origin. There is limited research on how Asian Americans use racial and national-origin cues (if any) in their vote choice. Tam notes that assuming a ‘pan-Asian’ hypothesis (i.e. a unified Asian preference for policy and candidates), is problematic (1995). In an analysis of candidate support for Mike Honda and Ro Khanna, Sadhwani finds that Honda, a Japanese American, received more support from Vietnamese. His opponent, an Indian American named Ro Khanna, received more support for Chinese and Indian voters in that district (2017; 2021).

‘It’s a Long Way from Kuusamo to Kuhmo’: Mapping Candidates’ Electoral Constituencies in the Finnish Open-List Single Preference Voting System

This article seeks an insight into the nature of intraparty competition in an open-list single preference voting system, and it does so by analysing the distribution of votes for Centre Party candidates in the 40 or so municipalities making up the northern Finnish constituency of Oulu in each of the five general elections between 2003 and 2019. It builds on Grofman’s distinction between a geographical constituency and a candidate’s electoral constituency to map the ecology of candidate support in a constituency with (1) a larger than average district magnitude (M); (2) a significantly larger than average territorial magnitude (T); and (3) a substantially larger than average Centre party magnitude (P). Setting M, T and P within a party organisational framework, the article identifies (1) a significant disparity between levels of intraparty competition at district and sub-district levels; (2) several contextual factors that act more as disincentives than incentives to engage in personal vote seeking across the electoral district.

LINE SEGMENT MATCHING ALGORITHM BASED ON FEATURE GROUPING AND LBD DESCRIPTOR

This paper proposes a line-matching algorithm based on feature grouping and a line band descriptor (LBD) to address the insufficient reliability of individual line descriptors for line matching. First, the algorithm generates line-pairs according to geometrical relationships such as the distances and angles between line segments extracted from a single image. Subsequently, the algorithm employs the epipolar line of intersection between two lines in a reference line-pair to constrain candidate pairs corresponding to the reference line-pair. Thereafter, each line in the reference line-pair is considered individually, and its support region and the corresponding support region of each candidate line in the candidate pairs are established, following which an affine transformation is used for unifying the sizes of the reference support region and the candidate support region. Moreover, the LBD descriptor is then used for describing the reference and candidate lines. The Euclidean distances between the reference line and each candidate line descriptors are calculated, and the nearest neighbor distance ratio (NNDR) is used as a criterion for determining the final matching. Finally, the one-to-many and many-to-one line correspondences in matching results are transformed into one-to-one line correspondences by fitting multiple lines to the new line; simultaneously, incorrect matches are eliminated. The experimental results show that the proposed algorithm yields reliable line-matching performance for close-range images.

When Do Voters Sanction Corrupt Politicians?

A growing body of research explores the factors that affect when corrupt politicians are held accountable by voters. Most studies, however, focus on one or few factors in isolation, leaving incomplete our understanding of whether they condition each other. To address this, we embedded rich conjoint candidate choice experiments into surveys in Argentina, Chile, and Uruguay. We test the importance of two contextual factors thought to mitigate voters’ punishment of corrupt politicians: how widespread corruption is and whether it brings side benefits. Like other scholars, we find that corruption decreases candidate support substantially. But, we also find that information that corruption is widespread does not lessen the sanction applied against corruption, whereas information about the side benefits from corruption does, and does so to a similar degree as the mitigating role of permissible attitudes toward bribery. Moreover, those who stand to gain from these side benefits are less likely to sanction corruption.