How might changes in the credibility of one alliance relate to the credibility of other alliance commitments? Debate between competing views on this question spans decades in part because systematic tests are difficult. We contribute systematic evidence with a new measure of credibility in U.S. alliances and novel technique to estimate interdependence. Our measure draws on expert ratings of allied beliefs over U.S. credibility and our analysis employs Gaussian process regression to analyze credibility. We find strong correlations in allied credibility perceptions within regions and little correlation across regions. Supplementary analyses suggest that these correlations reflect common unobservables and a small impact of shared perception of past U.S. behavior.

Social contact surveys, measuring who contacts whom, are widely used for epidemic intelligence and public health decision-making. Despite their widespread use, sample size calculations are not performed. We conducted a review of social contact surveys (2008–2025) to characterize current practice. We characterized the impact of survey size on epidemic metrics using two social contact surveys, the UK Social Contact Survey and POLYMOD (Europe), and two methods. For each dataset and approach, we generated repeated subsamples and calculated the resulting reproduction numbers, characterized their distributions, and measured uncertainty. We identified 107 unique social contact surveys from 57 studies. Sample sizes ranged from 30 to more than 10 000 participants, with a median of 1 438. One quarter of surveys contained fewer than 1 000 participants. Our analysis supports recruiting at least 1 000 participants for general-population social contact surveys used for epidemic modelling. Increasing sample size to 2 000 participants provides worthwhile gains in the precision of epidemic estimates, particularly for analyses using finer age stratification or individual-level approaches. Beyond approximately 3 000 participants, additional improvements in precision were small for the epidemic metrics analysed. This provides a practical balance between precision and participant burden.

How we measure racial bias matters. Previous literature demonstrates that direct questioning leads to unreliable responses. Scholars have thus developed a number of techniques to uncover racial bias without cuing a defensive response. I investigate the performance of text- and image-based factorial experiments in the case of racial motivation for opposition to new housing development relative to a more traditional list experiment. My results demonstrate that these often-used methods yield substantially different conclusions about the importance of racial biases in opposition to new housing construction. While the factorial experiments suggest little evidence of racial bias, the more traditional list experiment reveals that the potential for racial change in their neighborhood is a concern for a meaningful share of respondents.

Animal welfare is closely linked to human health and the environment. Over the last decade, One Welfare (OW) has emerged to address these connections. However, the academic research on OW, which integrates human well-being, animal welfare, and the environment, is still in its early stages, with limited insights into how it is perceived by supply chain actors. This study aims to explore how European citizens and other actors perceive the OW construct, particularly in relation to improved farm animal welfare. The data were collected in 2021 in two surveys conducted in nine European countries (Finland, the UK, France, Italy, Belgium, Germany, the Netherlands, Romania, and Denmark) targeted at citizens (n = 3,601) and other supply chain actors (n = 222). Exploratory factor analysis (EFA) and a non-parametric Kruskal-Wallis test were employed to analyse the perceptions among the countries. The results show that supply chain actors have a more multidimensional understanding of OW and farm animal welfare than citizens. Citizens viewed OW as a two-dimensional construct related to human well-being, farming success and food security, while supply chain actors perceived it as three-dimensional, also including issues related to environmental sustainability. Statistically significant differences were found across certain countries. For example, Italian citizens associated OW primarily with human well-being, while Romanian citizens linked it to farming success. However, both Italian and Romanian supply chain actors perceived food safety and environmental sustainability as most associated with OW. Understanding these perceptions is essential for developing policies that support public health, sustainability, and ethical practices across Europe.

Studies testing the relationship between preferences for Islamism and preferences for democracy in the Muslim world are inconclusive—and likely the result of measurement issues. Previously, we introduced a four-question battery measuring conceptions of Islamism and found that responses vary predictably across two components: whether respondents consider a shari‘a-based government to be one that provides services or one that imposes restrictive Islamic norms. Here, we demonstrate the consistency, generalizability, and utility of the battery through an analysis of 11,849 respondents in 11 Muslim countries. Defining a shari‘a-based government as one that provides is significantly and positively correlated with support for democracy, while defining it as a government that imposes is negatively correlated with these preferences across the entire sample.

How can we measure the effects of campaign events? We estimate how voters respond to a prominent campaign scandal—Donald Trump being convicted of 34 felony counts of falsifying business records—using data from a large, eight-wave panel study with waves fielded before, during, and after the verdict. We find the trial had virtually no effect on Trump supporters, even those who reported their support was conditional on an acquittal. We compare this precisely estimated null to estimates from popular cross-sectional methods, which fail to replicate it. The “change” question format estimates a 6% increase in support, while the “counterfactual” survey experimental design estimates a 10% decrease. We formalize the estimands each method estimates and discuss implications for the event study literature.

Social scientists often compare survey responses before and after important events to test how those events impact respondent beliefs, attitudes, and preferences. This article offers a formal analysis of such pre-event/post-event survey comparisons, including designs that seek to reduce bias using quota sampling, rolling cross-sections, and panels. Our analysis distinguishes major sources of bias and clarifies the comparative strengths and weaknesses of each approach. We then introduce a modified panel design—the dual randomized survey—to reduce bias in cases where asking respondents to complete the same survey twice could impact their Wave 2 responses. Our formalization of bias and novel research design improve scholars’ ability to study the causal impact of events through surveys.

In this note, we offer a cautionary tale on the dangers of drawing inferences from low-quality online survey datasets. We reanalyze and replicate a survey experiment studying the effect of acquiescence bias on estimates of conspiratorial beliefs and political misinformation. Correcting a minor data coding error yields a puzzling result: respondents with a postgraduate education appear to be the most prone to acquiescence bias. We conduct two preregistered replication studies to better understand this finding. In our first replication, conducted using the same survey platform as the original study, we find a nearly identical set of results. But in our second replication, conducted with a larger and higher-quality survey panel, this apparent effect disappears. We conclude that the observed relationship was an artifact of inattentive and fraudulent responses in the original survey panel, and that attention checks alone do not fully resolve the problem. This demonstrates how “survey trolls” and inattentive respondents on low-quality survey platforms can generate spurious and theoretically confusing results.

This study examines Hispanic formal volunteering and the cultural, social, and community context factors that affect their decision to volunteer. Using data from three surveys in the United States, the study finds that religious attendance, cultural background, and education are the most consistent and significant predictors of Hispanic formal volunteering. Religious attendance has a stronger positive impact on Hispanic volunteering than on non-Hispanics. The impacts of income, social resources, and community characteristics on Hispanics’ volunteering vary by surveys. Secular organizations serving children and youth and religious organizations are the favorite organizations for Hispanic volunteers.

Individuals seek food assistance from both government and nongovernmental services. The theory of voluntary sector failure asserts that governments act where nonprofits fail. How, if at all, does this theoretical approach provide insight into basic food provision through food pantries? We conducted a single embedded case study of one network of food pantry programs (n = 298) in one county of approximately 3 million people in the southwest of the USA. We used a survey (n = 137) to measure programmatic and organizational capacity and, then, categorized capacity measures into the four failure categories identified in the theory of voluntary sector failure. We found moderate to strong evidence of failure in all of the categories; however, we also argue that these data do not necessarily support the theory of voluntary sector failure. Two key nuances are identified.

What shapes attitudes toward wartime negotiation? Does exposure to violence lead citizens to take a hard-line approach to any peace settlements? Or does it make them more open to peace to make the violence stop? To answer these questions, we conducted a series of surveys and survey experiments in Ukraine in July 2022 and May 2023. First, using a series of survey experiments, we show that Ukrainians are flexible on certain issues, but others are considered red lines and not up for negotiation. Second, in the short-term, we find that exposure to violence does not turn Ukrainians against negotiations with Russia, in some cases, it makes them more amenable. Finally, over a longer duration of the war, we find that support for a negotiated solution drops. Our evidence suggests this drop is linked to exposure to violence and to beliefs about the war’s future course.

The partisan gap in economic perceptions flipped unusually dramatically after the 2024 U.S. presidential election: following the Republican victory, Democrats (Republicans) suddenly rated the economy much more negatively (positively). Was the resulting partisan difference a case of expressive responding, wherein surveys exaggerate partisan bias in measures of economic perceptions? In April 2025, I fielded a panel survey experiment that asked survey respondents to guess then-unpublished measures of economic growth, inflation, and unemployment in the current month or quarter (Prolific, N = 2,831). Randomly selected respondents were offered $2 per correct answer. Partisan bias did not shrink as a result, suggesting genuine differences in economic perceptions. Two measures of response effort (response time and looking up answers) increase, suggesting that misreporting does not fully explain the effects of pay-for-correct treatments.

Emotions and their sociopolitical impact have received increasing scholarly attention. However, it remains largely unclear whether emotional expression within surveys is subject to social desirability bias. By drawing on impression management theory and the disclosure decision model, I argue that emotional expression is likely prone to social desirability bias in interviewer-administered survey modes and test my hypotheses on mixed-mode ANES data. The findings demonstrate that respondents significantly underreport negative emotions—anger and fear—when interviewed face-to-face as compared to online. Furthermore, positive emotions, such as hope and pride, are not exempt from biased reporting related to interview mode. These results highlight the risks of estimating emotions and their salience by either relying on interviewer administration or combining survey modes.

Voters’ issue preferences are key determinants of vote choice, making it essential to reduce measurement error in responses to issue questions in surveys. This study uses a MultiTrait MultiError approach to assess the data quality of issue questions by separating four sources of variation: trait, acquiescence, method, and random error. The questions generally achieved moderate data quality, with 76% on average representing valid variance. Random error made up the largest proportion of error (23%). Error due to method and acquiescence was small. We found that 5-point scales are generally better than 11-point scales, while answers by respondents with lower political sophistication achieved lower data quality. The findings indicate a need to focus on decreasing random error when studying issue positions.

Travel accounts provide both benefits and challenges to survey archaeologists. This article presents a case study, generated by the Vayots Dzor Silk Road Survey, which aims to reconstruct the medieval (tenth to fifteenth centuries ad) landscape of Vayots Dzor in the Republic of Armenia, ‘excavating’ literary accounts of its landscape. Knowledge of this region in the Middle Ages is dominated by a core text written in the thirteenth century by Bishop Step’anos Orbelyan. From the mid-nineteenth century onwards, the region was visited by travellers who found links between the places they visited, the inscriptions they recorded, and the events and locations attested in Orbelyan’s text. Through examples from the site list of the Vayots Dzor Silk Road Survey, the authors explore how these and other sources accumulate, creating local knowledge about places that inform archaeologists and heritage professionals. They argue for reflection on the ways that local memory, archaeology, and the physical landscape inform complex makings of place.

Panel surveys and phone-based data collection are essential for survey research and are often used together due to the practical advantages of conducting repeated interviews over the phone. These tools are particularly critical for research in dynamic or high-risk settings, as highlighted by researchers’ responses to the COVID-19 pandemic. However, preventing high attrition is a major challenge in panel surveys. Current solutions in political science focus on statistical fixes to address attrition ex-post but often overlook a preferable solution: minimizing attrition in the first place. Building on a review of political science panel studies and established best practices, we propose a framework to reduce attrition and introduce an online platform to facilitate the logistics of survey implementation. The web application semi-automates survey call scheduling and enumerator workflows, helping to reduce panel attrition, improve data quality, and minimize enumerator errors. Using this framework in a panel study of Syrian refugees in Lebanon, we maintained participant retention at 63 percent four and a half years after the baseline survey. We provide guidelines for researchers to report panel studies transparently and describe their designs in detail.

As survey experiments have become increasingly common in political science, some scholars have questioned whether inferences about the real world can be drawn from experiments involving hypothetical, text-based scenarios. In response to this criticism, some researchers recommended using realistic, context-heavy vignettes while others argue that abstract vignettes do not generate substantially different results. We contribute to this debate by evaluating whether incorporating contextually realistic graphics into survey experiment vignettes affects experimental outcomes. We field three original experiments that vary whether respondents are shown a realistic graphic or a plain text description during an international crisis. In our experiments, varying whether respondents are shown realistic graphics or plain text descriptions generally yields little difference in outcomes. Our findings have implications for survey methodology and experiments in political science – researchers may not need to invest the time to develop contextually realistic graphics when designing experiments.