I checked 7 public opinion journals on Friday, October 30, 2026 using the Crossref API. For the period October 23 to October 29, I found 10 new paper(s) in 4 journal(s).

International Journal of Public Opinion Research

Competing agendas and public attention: zero-sum dynamics between personal and civic domains
Philemon Bantimaroudis, Iasonas Lamprianou
Full text
This study examines influences on public salience of social issues by exploring 2 streams of content described as the “personal domain,” along with a “civic domain” of human activity. To account for these distinctions in media content, we return to the established agenda—setting paradigm and its agenda-melding extension. The central proposition of the study is a zero-sum notion that positions the 2 domains in competition with one another. We expect that as social media users seek entertainment-oriented content of personal nature, their attention toward the civic domain diminishes. While analyzing data from Cyprus, we conclude that there is evidence of a zero-sum influence primarily for unobtrusive issues, with a political orientation. A similar finding does not apply for obtrusive issues.
Ideology at first sight: a comparative study of ideological stereotypes in four European countries
Gaetano Scaduto, Fedra Negri, Silvia Decadri
Full text
In recent years, research on political stereotypes has expanded, showing that trait-based associations about members of political groups are both pervasive and consequential for intergroup relations and polarization. Yet it is unclear which traits are more often involved in stereotypes about ideological groups. Moreover, this literature is overwhelmingly focused on the USA and severely lacks comparative evidence. This paper addresses these gaps by examining how sociodemographic, personality, and lifestyle characteristics are associated with citizens’ perceptions of others’ political ideology in Czechia, France, Italy, and Sweden. Findings from a conjoint experiment indicate that both sociodemographic and lifestyle traits, particularly professions and means of transportation, can inform citizens’ ideological perceptions. Conversely, personality traits demonstrate relatively limited influence. Comparative analyses reveal both common patterns and noteworthy heterogeneity: Sweden emphasizes class-related traits, France and Italy prioritize religious and age factors, while Czechia exhibits markedly distinct patterns.

Journal of Survey Statistics and Methodology

Structural Bias in Stylized Items with Point-Valued Categories
Ettore Scappini
Full text
Survey research frequently relies on stylized questions with discrete, ordered response categories to measure behaviors or attitudes. While these items simplify responses and facilitate standardization, they introduce a structural bias component (SBC) arising from the discrepancy between actual behavior and the assigned category values. This paper investigates SBC in the context of religious practice, using data from the European Values Study across multiple waves and countries. The analysis shows that the discrete nature of point-value items can generate distortions. A calibration model is proposed to estimate and adjust for this bias, assuming a uniform distribution of behaviors within each interval. Findings suggest that, while SBC can reach substantial levels in some domains—particularly where the accuracy of absolute values is crucial—in practice, however, its impact on theoretical interpretations or explanatory factors is typically limited. The study underscores the importance of carefully designing response categories and considering alternative scaling methods, such as stylized items with interval-valued categories, to reduce measurement error and enhance survey validity.
Does Respondent Gender Matter to the Collection of Household Consumption and Expenditure Data in India?
Sharan Sharma, Pallavi Choudhuri, Sonalde Desai
Full text
Consumption and expense (CE) data from surveys in low-and-middle-income countries (LMICs) are critical to understand social inequalities, formulate policies, and implement targeted benefits. However, little research has examined measurement error in these data. This paper investigates one potential source of measurement error: the respondent’s gender. This is important given the sharp differences in gender roles, attitudes, experiences, and identities in LMICs that may result in different responses from male and female respondents. We analyze CE values from 34 items that were collected from a recent large-scale survey of more than 46,000 households in India; females were respondents in 37 percent of these households. We use multigroup confirmatory factor analysis to examine if data from male and female respondents have measurement equivalence. We then use zero-inflated gamma models to investigate if respondent gender is associated with the prevalence of zero values and the magnitude of non-zero values, using propensity weights to adjust for possible selection biases. Results show that while most CE categories exhibit gender effects, effect sizes are generally modest. The effect magnitudes vary by CE category, and in general, female respondents are associated with more zeros and lower non-zero response values compared to male respondents. However, categories say annual education expenses or 30-day medical expenses see a larger average value for females compared with males. We find that the role of the respondent in shopping for the household and managing its expenses partially explains gender effects. The respondent’s age and education, and help received in answering the CE questions, moderate gender effects on non-zero CE values. We suggest avenues for future research and implications for survey practice.
Small Area Estimation Using Area-Level Linked Data
Enrico Fabrizi, Nicola Salvati, Ray Chambers
Full text
Official statistics increasingly use linked survey and administrative data for small area estimation, but record linkage error can distort direct estimators in area-level Fay–Herriot models. We develop a likelihood-based framework for such models under an Exchangeable Linkage Error mechanism, using the Missing Information Principle to obtain linkage error-adjusted maximum likelihood estimators of regression coefficients and variance components, an empirical best predictor of true area means, and a mean squared error estimator. Simulation results show that ignoring linkage error leads to substantial bias and loss of efficiency, while the proposed methods restore unbiasedness and provide accurate uncertainty quantification. An application to estimation of average equivalized income for 113 labor market areas in Central Italy, based on European Union Statistics on Income and Living Conditions (EU-SILC) data linked to administrative registers, illustrates the practical benefits of the approach.

Public Opinion Quarterly

Investigating the Utility of LLM-Based “Silicon Samples” in Political Science Conjoint Experiments
Alice Malmberg
Full text
This research note is the first study to explore the viability of using LLM-generated respondents in forced-choice conjoint experiments. I generate naive “silicon samples” using three models, GPT 4o-Mini, Llama 3.2, and Magistral-small-2506, benchmarked to a large sample of live conjoint respondents, allowing for direct comparisons between human and silicon choices. The resulting analyses suggest that naively generated silicon samples are insufficient to simulate human decision-making in conjoint tasks; these results also suggest that there are systemic differences in the way demographic covariates shape LLM and human choices in experimental contexts. In total, this analysis makes two important contributions: it establishes a descriptive baseline understanding of LLM-generated respondent performance in conjoint experiments and suggests that naive silicon samples cannot accurately infer human choices using demographic traits in experimental decision making contexts. Finally, the implications of these results imply that LLMs consider covariates differently than live respondents do in micro-level decision making contexts.
Do Gender-of-Interviewer Effects Differ Across Immigrant Generations? Survey Evidence from Italy
Christina Sarah Hauser
Full text
Interviewer gender has been shown to affect responses to survey questions on gender attitudes and norms, but does its influence vary across groups with different migration backgrounds? I study this question using the Between Origin and Destination (BOnD) survey, conducted in Lombardy, Italy, between 2024 and 2025. Consistent with gender-of-interviewer effects, a type of social desirability bias, female interviewers elicit more progressive responses on a summary index of gender norms and on an index of the acceptability of homosexuality, abortion, divorce, casual sex, and premarital sex. The effect is concentrated among natives and second-generation individuals; first-generation immigrants show little response to interviewer gender. One possible explanation is that social desirability pressure from a female interviewer operates through host-country social norms: Individuals more embedded in the Italian normative context are more responsive to cues from a female interviewer. These findings have implications for the design of surveys administered to mixed native-immigrant populations.

Social Science Computer Review

Pathways Out of Cybercrime: Perceived Desistance From Criminal Hacking
E. Rutger Leukfeldt, Luuk M. J. Bekkers
Full text
The present study seeks to understand how criminal hackers self-report to desist from the world of cybercrime. In doing so, we address significant gaps in criminological literature, as little is known about pathways out of cybercrime offending. Interviews were conducted with 22 individuals involved in cyber-dependent crime, primarily from the Netherlands. Of these, 15 respondents were justice-involved youth and 7 respondents self-identified as criminal hackers. The interviews offer unique insights into the stages offenders navigate following their involvement in cybercrime. Findings reveal that young hackers may be susceptible to behavioral change through various mechanisms. Desistance from cybercrime is a process that warrants a multidisciplinary perspective, influenced particularly by social bonds, prosocial daily routines, and deterrent experiences. A combination of police intervention and alternative approaches that emphasize ethical application of skills may be a promising route for young hackers in particular, although actual intervention effects remain unverified. We encourage evaluations of current programs for hackers as well as additional quantitative assessments of protective factors among cybercrime offenders.
The Cost of Capturing: How Smartphone Photo-Taking Alters Memory Performance and Cognitive Self-Esteem: The Role of Smartphone Self-Expansion
Tianke Che, Wenxin Xu, Xiaochun Xie
Full text
Taking photos to manage memories with smartphones is a routine strategy in the digital era. However, it remains unclear how smartphone photo-taking affects memory performance and self-evaluation. This research examined whether smartphone photo-taking is associated with a pattern consistent with the “Google effect,” and whether these associations vary with self-expansion via smartphone use. Across three experiments ( N = 363), participants photographed or observed materials before completing memory tests and measures of cognitive self-esteem. Study 1 tested the basic photo-taking effect; Study 2a examined device ownership as a contextual proxy for smartphone self-expansion; and Study 2b examined trait self-expansion as a continuous moderator. Results showed a photo-taking-impairment effect on memory, alongside higher cognitive self-esteem following photo-taking. Moreover, higher smartphone self-expansion was associated with stronger increases in cognitive self-esteem and greater memory overestimation, whereas its role in objective memory impairment remained inconclusive. Altogether, the findings suggest that smartphone photo-taking can reduce memory performance while increasing cognitive self-esteem.
Surveillance Path Dependence: Technological and Institutional Lock-In of Digital Surveillance Infrastructures in China
Jingyang Huang, Jack Linzhou Xing
Full text
Digital surveillance infrastructures are widely critiqued for their use-side problems of access, privacy, and discrimination, but meaningful intervention requires understanding how these infrastructures are developed and stabilized in the first place. This paper examines China’s health code systems (HCSs) as a revelatory case of path dependence in the development of digital surveillance infrastructures. Drawing on news, first-hand interviews, and fieldwork, we trace how local governments chose to embed contact-tracing systems within the pre-existing digital ecosystems of Alipay and WeChat, primarily at the local level. Such choices persisted despite the central government’s openly cautious stance toward private tech giants and its subsequent attempts to develop independent alternatives. We describe this trajectory as surveillance path dependence, in which the convergence of pre-existing technological foundations, tight temporal pressure, and institutional incentives within a fragmented authoritarian institutional context locked new applications into established digital surveillance paths. This study suggests that mitigating the adverse societal impacts of large-scale digital surveillance requires intervening directly in the foundational design and institutional deployment of digital ecosystems rather than at the level of use-side effects.