I checked 7 public opinion journals on Monday, March 09, 2026 using the Crossref API. For the period March 02 to March 08, I found 6 new paper(s) in 2 journal(s).

Journal of Official Statistics

Measuring Risk of Re-Identification for a Nonprobability Sample Using a General Reference Sample
Natalie Shlomo, Minsun Riddles, Tom Krenzke
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Estimating the risk of re-identification probabilistically is well-developed for the case of a random representative sample drawn from the general population, such as large-scale government surveys conducted regularly at National Statistical Institutes. Recent work extended this procedure to assess the risk of re-identification in non-probability subpopulation registers such as a cancer register. In this paper, we extend this work further to the case of samples drawn from registers or more generally to non-probability samples, such as those used in opt-in panels at survey organizations. The assumption is that membership to the subpopulation register is not known and the sampling mechanism is also unknown. We show how to assess the risk of re-identification for these types of non-probability samples using a probability-based reference sample to infer population parameters under the probabilistic modeling framework. We demonstrate with a simulation study and a real application on the 2021 Survey of Doctoral Recipients drawn from a subpopulation register of all PhD recipients from an accredited US institution.

Public Opinion Quarterly

Blame Shifting in Presidential Systems: Ministerial Terminations’ Corrective Effect on Approval
Bastián González-Bustamante
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How do ministerial terminations affect presidential approval? Presidents face unexpected challenges related to stochastic events such as scandals, policy failures, or economic crises. We argue that the termination of ministers who have received calls for their resignation presents an opportunity for the president to send signals to the electorate in the expectation of a corrective effect on popularity through a blame-shifting dynamic. The central argument is that this dynamic occurs only in coalition governments where political responsibility may be more easily attributed to the coalition’s different parties and factions, weakening personalization centered on the president and facilitating blame shifting and the corrective effect. The expectation of a corrective effect on approval is tested using instrumental variables (IV) regressions applied to novel data on ministerial terminations and resignation calls in 124 governments in 12 presidential democracies. The data were gathered by combining data mining, machine-learning techniques, and survey marginal time series based on the dyad ratios algorithm for approval. The main findings support the expectation that individual terminations of tainted ministers generate a corrective effect of nine points on presidential approval in coalition governments, which decreases in the medium and long term.
How to Measure Public Support for Political Violence
Nathan P Kalmoe, Lilliana Mason
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With low but rising levels of violent political threats and violent acts by civilians in the United States, researchers increasingly want to measure violent public views—fearing the erosion of collective norms inhibiting violence while also regarding individual attitudes as a risk for rare violent action and more common forms of aggressive political behavior. But how should violent views be measured and interpreted? Drawing on our decade-plus researching these views with several dozen questions and a catalogue of related work by others, we provide a practical measurement guide for assessing violent political views with extensive new observational and experimental illustrations that also make important methodological and substantive contributions to the field. We provide considerations for choosing good measure(s): empirically informed measurement principles, general and specific question evaluations, a deep dive into question design, reliability, and validity, and more. The Supplementary Material also catalogues a century of violence questions and more published works.
Unwilling to Disclose: Privacy and Pregnancy in Post- Roe America
Cindy D Kam, Colette Marcellin
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On June 24, 2022, the Supreme Court overturned Roe v. Wade and ended the constitutional right to abortion across the United States. The Dobbs decision created a disrupted and fragmented policy environment, with significant losses of reproductive rights in some US states and high levels of uncertainty in others. We analyze data from the nation’s premier health survey to examine whether Dobbs influenced women’s willingness to disclose whether they are pregnant. We find that women became more likely to refuse to disclose their pregnancy status in the wake of the Dobbs decision. This effect emerges most strongly among younger women and among those living in states where abortion rights were not actively threatened. Our results suggest that Dobbs may have reduced women’s willingness to share their pregnancy status through presenting policy change threat, with concerning implications for survey research, health policy, and women’s health.
Ideological Cues, Partisanship, and Prejudice Against LGBTQ Judges
Andrew R Stone, Tony Zirui Yang
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How does the gender and sexual identity of a prospective judge shape public support for their nomination? We build upon recent scholarship on instrumental inclusivity and argue that, after accounting for nominee ideology, Americans of all partisan stripes will penalize LGBTQ nominees. Using a conjoint experiment, we randomly vary a prospective Biden US Supreme Court nominee’s gender and sexual identity. Crucially, we also randomize the nominee’s ideology, enabling us to disentangle LGBTQ identity from the ideological signal it sends and differentiate between genuine and instrumental support for LGBTQ nominees. Contrary to recent findings suggesting that Democrats reward minority judges, we find that respondents from both parties penalize LGBTQ nominees. The magnitude of these effects—roughly 14 percentage points for transgender nominees and 8 percentage points for gay or lesbian nominees—is considerable and second only to shared partisanship. Our study underscores that ideological alignment does not necessarily foster genuine inclusivity for LGBTQ individuals and highlights the persistent challenges of representation for marginalized groups in an era of polarized judicial nominations.
Reassessing Support for Political Aggression and Violence in the United States
Scott Clifford, Lucia Lopez, Lucas Lothamer
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Recent events have driven a surge in scholarly attention to public support for political violence in the United States. Yet, research paints a conflicting picture about the levels and correlates of support for violence. We argue that these disagreements are partly due to researchers’ measurement choices. After reviewing common practices and identifying measurement challenges, we introduce a measure designed to overcome these problems that allows respondents to choose their target of aggression. Across multiple studies, we compare our measure to two common alternatives. While we find similarities, our measure uncovers substantially more support for aggression and violence, particularly among weak partisans, holding implications for the levels and correlates of support for aggression. Further, by design, our measure provides information about the type of aggression that is endorsed and the most common targets. We conclude with recommendations for researchers studying support for political aggression.