I checked 7 public opinion journals on Friday, April 24, 2026 using the Crossref API. For the period April 17 to April 23, I found 10 new paper(s) in 4 journal(s).

Journal of Survey Statistics and Methodology

BART-FH: Flexible Nonlinear Modeling for Small Area Estimation
Paul A Parker, Abdulhakeem Eideh
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The Fay-Herriot model has been the workhorse of area-level small area estimation. This model links direct survey estimates to area-level covariates through a linear mixed-effects framework. While effective, this model assumes a linear relationship between covariates and the true area-level quantities, limiting its flexibility in capturing complex patterns inherent in real-world data. In this work, we introduce an extension of the Fay-Herriot model that integrates Bayesian Additive Regression Trees (BART) to model the true area-level quantities as nonlinear functions of the covariates, complemented by an additive random effect to account for unexplained heterogeneity. The proposed BART Fay-Herriot (BART-FH) model leverages the nonparametric capabilities of BART to capture intricate nonlinear relationships and interactions among covariates, offering a more flexible alternative to traditional linear models. To evaluate the performance of the BART-FH model, we conduct an empirical simulation study comparing its estimation accuracy and predictive capabilities against the standard Fay-Herriot model. Furthermore, we apply the BART-FH model to household income data from the American Community Survey (ACS).

Politics, Groups, and Identities

Does political identity rhetoric influence individual political attitudes? An experimental survey in the Chinese context
Hongbo Yu, Hsin-Che Wu
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Public Opinion Quarterly

James L. Gibson. Democracy’s Destruction: Changing Perceptions of the Supreme Court, the Presidency, and the Senate after the 2020 Election
Hillary Style
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Leader-Motivated Behavior: Voting by Mail in the 2020 General Election
Seth C McKee, Enrijeta Shino, Daniel A Smith
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There is a large body of scholarship that probes the association of elite messaging and motivated reasoning with political behavior. Few studies, though, consider how these factors relate to validated mass behavior. Leveraging two national surveys, we assess voter alignment with President Trump and who voted by mail (VBM). Drawing on 2016 and 2020 Cooperative Election Study (CES) data, we analyze the likelihood that Trump supporters: (1) voted by mail, (2) self-reported voting by mail, and (3) self-reported not voting by mail when they did (misreporting VBM). In 2016, candidate Trump spoke of a “rigged” election, but it was in the 2020 contest that President Trump indicted VBM as the principal reason he might lose reelection. Analyzing VBM before (2016) and during (2020) Trump’s attack on this vote method suggests that leader opinion activation shaped the views of Trump voters and their actual voting behavior. In 2020, Trump supporters were markedly less likely to cast a VBM ballot and were also significantly more likely to disclaim voting by mail when they actually did. These findings have important implications regarding the extent to which purported and verified mass political behavior comports with leader-directed messaging.
Reluctant Partisans, Not Undercover Partisans: Why Americans Increasingly Identify as Independent
Alex Tolkin
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In the United States, partisanship has a greater impact on political behavior than any other social identity. However, the proportion of Americans who actively identify with a party, as opposed to Independents who “lean” toward one, is at its lowest point in decades. Existing research offers two explanations for why: First, being seen as partisan is not socially desirable, so people identify as Independent despite covertly preferring one party. Second, nonidentification may be a result of viewing both parties negatively. Using eight waves of panel data from 2016 to 2022, I compare the strength of these competing explanations. I only find support for the explanation-based evaluations of the parties. People switch from partisans to Independents when they view their former party more negatively, not when they seek to make a good impression.
Gender-of-Interviewer Effects in the Measurement of Gender Attitudes: Lessons from 18 Countries of the European Social Survey
Ádåm Stefkovics
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Measuring gender-related questions in face-to-face surveys can be challenging due to the potential influence of the interviewer’s gender. First, people may feel more comfortable disclosing sensitive information (e.g., gender-based discrimination) to a female interviewer or an interviewer of the same gender. Second, respondents may alter their responses in light of what they perceive as desirable, for instance, by reporting more feminist views when interviewed by a female interviewer. To test these assumptions, we use the gender module of the eleventh round of the European Social Survey. We analyze patterns from 28,567 respondent-interviewer dyads from 18 countries. We find no evidence of the interviewer’s gender influencing disclosure and limited evidence of gender-of-interviewer (GOI) effects on distributions. These findings are consistent across countries with varying levels of gender equality. Our results indicate that in European societies, GOI effects may not cause significant harm in social surveys.
Is There a Partisan Divide in Citizens’ Preferences on Ukraine Support? Survey-Experimental Evidence from the US
Lukas Rudolph
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Models of democratic responsiveness imply that consistent US foreign policy is furthered by bipartisan agreement on core US strategy. A broad literature indicates, however, that politics does not stop “at water’s edge,” suggesting relevant differences between more “dovish” Democratic-leaning and more “hawkish” Republican-leaning voters. I revisit this question for the case of US support strategies aiding Ukraine against the Russian invasion in 2022. In particular, I investigate the extent of partisan differences in both overall agreement and the hard trade-offs between competing normative, strategic, and economic considerations connected to supporting Ukraine. Do Democratic- and Republican-leaning voters deal with these trade-offs differently? I bring conjoint and vignette survey experimental evidence from 2,334 US citizens to this question. I show that absolute levels of support for Ukraine are lower among Republicans. However, irrespective of partisanship, citizens resolve the fundamental trade-offs involved in Ukraine policy similarly. Strategies that sustain Ukraine’s territorial integrity and political sovereignty, rather than concessions to Russia, are substantively more likely to be chosen, irrespective of partisanship, even if less strongly so among (moderate) US Republicans. Both Democratic and Republican voters show similarly high concern for the human costs of war, domestic economic costs, and escalation risk—with economic costs resonating more among Republicans. These results imply that for a case where both normative and strategic motivations for intervention loom large, public support is not structured as expected from “partisan types.” Tentatively, this indicates that differences in partisan preferences are no constraint for persisting US support to Ukraine.

Social Science Computer Review

Writing as an 18th-Century Automaton
Julie Park
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This essay conceives artificial intelligence as a chapter in the history of writing through reconsidering the eighteenth-century automaton writer created by Jaquet Droz, a Swiss clock making workshop. As much an innovation in writing technology as it was an early example of artificial intelligence, the Jaquet Droz automaton writer reveals how artificial intelligence is a historical idea and material artifact deeply entangled with the history of writing, an embodied as well as deeply emotional form of cognitive activity and one of the oldest human technologies.
The Human Soul and its Deceptions: Early Modern Imitation Games
Jonathan Regier
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Early modern writers had much to say about how humans and other animals compared to machines. RenĂ© Descartes (1596–1650) argued that an automaton could never convincingly impersonate human intelligence, however lifelike it seemed. To set the stage, I will briefly discuss Descartes’ imitation game, along with its philosophical and theological motivations. I will then move on to another imitation game conceived of by Nicolas Filleau de la Chaise (1631–1688), who asked whether a human could successfully imitate a machine. Finally, I will reflect on how Thomas Hobbes (1588–1679) portrayed the mechanical intelligence of the state as a safeguard against the deceptions of its enemies.
Data Donation: A First Step Towards Improving Representativeness in Algorithmic Hiring Datasets
Jorge Saldivar, Jessica Wulf, Carlos Castillo
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The use of algorithmic hiring is on the rise, becoming more and more common due to its capacity to process a large number of applications with efficiency. Despite the advantages of this approach, there have been numerous cases of discriminatory hiring outcomes. A significant contributing factor to such outcomes is the lack of representativeness in the data used to develop these systems. This results in a significant decline in performance for underrepresented groups, disproportionately impacting marginalized communities. Addressing bias in algorithmic hiring requires access to comprehensive datasets that include curriculum vitae (CV) and demographic information reflecting diverse backgrounds. Unfortunately, there is a lack of datasets that serve such a purpose. This paper introduces a data donation campaign designed to collect real-world CVs, including demographic and sensitive information, from a representative sample of individuals in the EU workforce. The paper discusses the design decisions underpinning the campaign, along with the challenges encountered during its deployment and execution. Finally, it offers lessons learned and practical solutions to overcome these challenges, thereby contributing valuable insights for future efforts in this domain.