I checked 7 public opinion journals on Saturday, July 25, 2026 using the Crossref API. For the period July 18 to July 24, I found 7 new paper(s) in 4 journal(s).

International Journal of Public Opinion Research

Impunity and coordination under polarization: public legitimacy and anti-corruption enforcement
Carlos Pereira, Mariana Furuguem, Frederico Bertholini
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The lack of coordination among accountability institutions is widely recognized as a driver of elite impunity in democratic systems. At the same time, enhanced coordination among prosecutors, judges, and enforcement agencies can raise concerns about due process and judicial impartiality. This article examines how political polarization shapes citizens' evaluations of institutional coordination in anti-corruption efforts. Using Brazil's Lava Jato operation as an empirically salient and ideologically charged context, we field a web-based survey experiment that assesses public support for a hypothetical legislative reform designed to increase coordination among accountability institutions while explicitly acknowledging its potential legal trade-offs. We show that citizens broadly support coordination even when informed of possible risks to defendants' rights. However, when coordination is explicitly associated with Lava Jato, ideological polarization structures these evaluations: right-wing respondents become more supportive of coordination, while left-wing respondents become more skeptical. We argue that polarization shifts the object of legitimacy from judicial outcomes to institutional design, transforming coordination itself into a contested political object. The findings identify a mechanism through which polarization constrains the public legitimacy—and, thus, the political feasibility—of institutional reforms aimed at combating corruption.

Journal of Elections, Public Opinion and Parties

Black and Latino American support for cross-ethnic coalitions: evidence from two conjoint experiments
Kenicia Wright, Güneş Murat Tezcür
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Subnational electoral accountability in multilevel emerging democracies. Gubernatorial voting behavior in Argentina
Germán Lodola, Tomás Ciocci Pardo
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Affective polarization and electoral turnout: testing the moderating role of political sophistication on the Italian case
Antonino Castaldo, Danilo Di Mauro, Vincenzo Memoli
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Journal of Official Statistics

Strengthening Digital Survey Implementation for Official Statistics Using Text Mining: Evidence from Feedback Dataset of the Digital Domestic Tourism Survey 2024
Hanun Nabila Azis, Erna Nurmawati, Teguh Sugiyarto, Eko Rahmadian
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The shift toward non-traditional data sources has made Mobile Positioning Data (MPD) a key tool for more flexible and scalable data collection. By utilizing SMS-to-web invitations from network providers, this method improves coverage, timeliness, and cost efficiency, though it still faces hurdles regarding response rates, respondent burden, and respondent trust. This study analyzes respondent feedback from the Digital Domestic Tourist Survey 2024 using sentiment analysis and topic modeling. The most frequently discussed aspects were survey application reliability (64.48%), web questionnaire presentation (63.53%), perceived ease of use (63.09%), and questionnaire content (59.80%). Positive sentiment dominated all aspects, accounting for at least 61% of responses, indicating an overall favorable perception. Topic modeling of survey question variables produced a coherence score of 0.4199. Higher coherence was observed for the positive sentiment dataset (0.5447) compared to the negative sentiment dataset (0.4869), suggesting a well-structured alignment with the study’s framework. Despite the generally positive evaluation, improvements are needed in application reliability, questionnaire design, incentive clarity, data collection methods, and communication strategies to reduce respondent burden, and enhance participation in MPD-based SMS-to-web surveys.

Journal of Survey Statistics and Methodology

Using Opt-In Non-Probability Surveys to Estimate COVID-19 Infection and Vaccination Rates
Alexi Quintana-Mathé, Ata A Uslu, Jason Radford, James N Druckman, Kristin Lunz Trujillo, Alauna Safarpour, Katherine Ognyanova, Matthew A Baum, Jonathan Schulman, Roy H Perlis, Mauricio Santillana, David Lazer
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Public health crises demand timely surveillance of disease and interventions. This was a substantial challenge during COVID-19 in the United States due to the federalized response. States varied widely in infection and vaccination rates. Continuous state-level probability samples for tracking were unavailable and would have been logistically and financially onerous. Administrative data eventually became inaccurate. We thus evaluate the accuracy of large-scale opt-in non-probability state and national samples (from the Covid States Project) that estimated infection and vaccination rates on a near-continuous basis. The estimates aligned closely with a high-quality national probability sample and state-level administrative data (when such data were reliable). We offer evidence that the success of the surveys, compared to other less accurate non-probability surveys, may have stemmed from the successful recruitment of respondents with low trust in health institutions (i.e., individuals who often avoid surveys). We conclude by discussing how the Covid States Project can inform further data collection efforts requiring extensive spatial and temporal coverage.
The Relevance of Internet-Related Characteristics in Explaining Online Panel Participation and Designing Nonresponse Adjustments. Evidence from a Mixed-Mode Experiment in Recruiting A Probability-Based Online Panel
Jessica M E Herzing, Barbara Felderer
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The transition to online data collection in social science research offers benefits such as lower costs and faster data collection, but also brings challenges, particularly in terms of nonresponse bias related to digital inequality characteristics. People with less pronounced Internet-related characteristics and thus low digital skills or privacy concerns are often unwilling to participate in online panels, which is often a source of bias in survey results. Using data from the 2018 German Internet Panel recruitment experiment, we investigate whether offering an offline recruitment mode attracts respondents with less pronounced Internet-related characteristics, whether these characteristics affect online panel participation, and how including Internet-related characteristics in nonresponse weighting can help improve nonresponse adjustments. Our results show that mixed recruitment strategies that offer a paper-based recruitment survey initially attract individuals with less salient Internet-related characteristics, thereby mitigating their underrepresentation in surveys that offer only an online recruitment survey. In addition, the inclusion of Internet-related characteristics in the nonresponse weighting of the online panel improves estimates for several substantive variables.