Trust in civil servants is essential for effective governance, enabling policy implementation, public service delivery, and compliance. However, the lack of comparable cross-national data on trust in bureaucracy has limited our ability to systematically examine these relationships. To address this gap, we develop the Trust in Civil Servants (TCS) dataset using an advanced latent-variable modeling technique, using 132 national and cross-national surveys from 98 countries (1986-2022). Our measures reveal variations in trust both within and between countries. We find that economic performance and public security enhance trust in the short term, whereas government quality and effectiveness have more enduring, long-term impacts on trust in civil service. The TCS dataset opens new avenues for examining connections between trust, governance quality, and complex policy challenges across different contexts.

Prominent recent works have measured democratic support using a single latent variable that purports to span a single dimension from steadfast opposition to whole-hearted support. This ignores ample evidence that support for democracy is complex and multidimensional. Here we provide a series of validation tests of the sort of cross-national time-series latent variable measures employed in recent research by reference to questions on support for liberal democracy and opposition to its erosion from multi-wave surveys conducted around the world. These tests show that, across countries and years, this latent variable is nearly orthogonal to measures of support for contestation and participation; civil liberties; institutional constraints on executive power; and prioritizing democracy over the economy, economic equality, or order. We conclude that support for democracy in any robust sense is simply not well captured by one-dimensional latent variable. Such measures are powerful but researchers must be mindful of their limitations.

As the need to address climate change grows increasingly pressing, so does the need for understanding the factors that undermine public support for mit- igation. One prominent recent analysis of three cross-national surveys argues that people—especially men—in richer countries express less concern for cli- mate change and see more costs and fewer benefits to mitigation, pointing to compensation as a potential solution. Drawing on hundreds of surveys, this reassessment employs a series of meta-analyses to reveal that while gender differences in climate concern are indeed larger in richer countries, both men and women express more concern in such settings relative to poorer countries, and there is no relationship between economic development and gender differ- ences in mitigation’s perceived costs and benefits. Instead, gender differences in climate concern are mirrored in differences in concern across a wide array of risks, consistent with more widespread masculine performative fearlessness in richer countries.

The extent to which the public takes an interest in politics has long been argued to be foundational to democracy, but the want of appropriate data has prevented cross-national and longitudinal analysis. This letter takes advantage of recent advances in latent-variable modelling of aggregate survey responses and a comprehensive collection of survey data to generate dynamic comparative estimates of macrointerest, that is, aggregate political interest, for over a hundred countries over the past four decades. These macrointerest scores are validated with other aggregate measures of political interest and of other types of political engagement. A cross-national and longitudinal analysis of macrointerest in advanced democracies reveals that along with election campaigns and inclusive institutions, it is good economic conditions, not bad times, that spur publics to greater interest in politics.

Income inequality is one of the most important measures to indicate socioeconomic welfare and quality of life, and has implications for the environment. Yet, especially at the subnational level, comprehensive global data on income distribution are widely missing. Such data are essential for assessing patterns of inequality within countries and their development over time. Here we created seamless global subnational Gini coefficient and gross national income purchasing power parity per capita datasets for the period 1990–2023 and used these to assess the status and trends of income inequality and income, as well as their interplay. We show that while gross national income has increased for most people globally (94%), inequality has also increased for around 46–59% (depending on the national dataset used) of the global population, while it has decreased for 31–36% and has not shown a significant trend for 10–18%. We illustrate heterogeneities in inequality trends between and within countries, analyse plausible confounding factors related to inequality, and highlight the broad utility of the datasets through a case study that investigates correlations with terrestrial ecological diversity. Our dataset and analyses provide valuable insights for relevant stakeholders to direct future research and make informed decisions at the global, national and subnational levels, addressing societal, economic and environmental challenges caused by inequality.

Support for gay rights has increased in the publics of many countries over recent decades, but the scholarship on the topic has been hindered by the limited available data on these trends in public opinion. To overcome this problem, we present the Support for Gay Rights (SGR) dataset, which combines a comprehensive collection of survey data with a latent-variable model to provide annual time-series estimates of public support for gay rights across 118 countries and over as many as 51 years that are comparable across space and time. We show these data perform well in validation tests and demonstrate their potential by replicating the influential but recently questioned finding of Andersen and Fetner (2008) that more income inequality yields less tolerant and supportive attitudes toward gay people. We anticipate that the SGR data will become a crucial source for cross-regional, cross-national, and longitudinal research that improves our understanding of the sources and consequences of public support for gay rights.

Income inequality is one of the most important measures to indicate economic health, social justice, and quality of life. Yet, especially at the subnational level, comprehensive global data on the distribution of incomes is widely missing. Such data is essential to assess patterns in inequality within countries and their development over time. We created seamless global subnational Gini coefficient and gross national income (GNI) PPP per capita datasets for 1990-2021 and used these to assess the status and trends of income inequality and income as well as their interplay. We show that while gross national income has increased for most (96%) people globally, inequality has also increased for around 68% of the global population. We illustrate heterogeneities in inequality trends between and within countries and analyse plausible confounding factors related to inequality. Our dataset and analyses reveal new insights into the issue, opening novel research avenues at the global, regional or national level and providing comprehensive evidence for policymakers to make informed decisions.

Do democratic regimes depend on public support to avoid backsliding? Does public support, in turn, respond thermostatically to changes in democracy? Two prominent recent studies (Claassen 2020a; 2020b) reinvigorated the classic hypothesis on the positive relationship between public support for democracy and regime survival-and challenged its reciprocal counterpart-by using a latent variable approach to measure mass democratic support from cross-national survey data. However, both studies used only the point estimates of democratic support. We show that incorporating the concomitant measurement uncertainty into these analyses reveals that there is no support for either study's conclusion. Efforts to minimize the uncertainty by incorporating additional survey data still fail to yield evidence in support of either hypothesis. These results underscore the need for both more nuanced analyses of the relationships between public support and democracy and taking measurement uncertainty into account when working with latent variables.

Prominent recent work argues that support for democracy behaves thermostatically---that democratic erosion boosts democratic support while deepening democracy yields public backlash---and further contends that there is no evidence for the classic argument that democracy itself increases democratic support over time. Here, we document how these conclusions depend on subtle choices in measurement coding that constitute 'researcher degrees of freedom': analyses employing alternative reasonable choices provide little or no support for the original conclusions. The fragility of the statistical results demonstrates that researcher degrees of freedom in measurement must be taken seriously and that the question of the relationship between democratic institutions and democratic support remains unsettled.

Public discontent with the political system has become an increasingly salient concern in recent years, with the argument that it undermines democratic stability and effective governance. Nevertheless, the understanding of the nature, trends, and drivers of political discontent remains debated, largely reflecting the constraints from available survey data and items in the construction of measurement. This article takes advantage of the state-of-the-art latent-variable modeling to aggregat survey responses and a comprehensive collection of survey data to generate dynamic comparative estimates of public political discontent (PPD) for over a hundred countries over the past four decades. These PPD scores are validated with responses to the individual source-data survey items that were used to generate them as well as the democratic evaluation survey item that was not used in our estimation. Next, a cross-national and longitudinal analysis of PPD in advanced democracies (i.e., OECD countries) highlights that public political discontent has been on a rising trend, rather than merely “trendless fluctuations” as (Norris 2011) claimed. Our results reveal that these increased discontents are largely attributable to worsening economic conditions, including low average income, slow growth, and high unemployment rates.

Societal attitudes toward gender roles in the workplace and politics play a central part in theorizing on the difficulty women face in achieving political equality, but shortcomings in the available data have prevented direct examination of many implications of these theories. Drawing on recent advances in latent variable modeling of public opinion and a comprehensive collection of survey data, we present the Public Gender Egalitarianism dataset to address this need: comparable estimates of the public’s attitudes on gender equality in the public sphere across more than one hundred countries over time. These PGE scores are strongly correlated with responses to individual survey items and with women’s rates of participation in the labor force and corporate boards. We expect that the PGE data will become an invaluable source for broadly cross-national and longitudinal research on the causes and consequences of collective attitudes toward gender equality in the public sphere.

Data 'janitor work', the task of getting data into a format appropriate for analysis, has grown increasingly important as political science research has come to depend on data drawn from hundreds and thousands of sources. One tempting solution is to simply enter the data by hand, but this approach raises serious risks of data-entry error, a difficult-to-catch problem with the potential to fatally undermine our conclusions. Underscoring these points, we identify data-entry errors in a prominent recent article, the 2020 study by Claassen that examines the effect of changes in democracy on public support for democracy. We then show that when these errors are corrected, the work's models provide no support for its conclusion that publics react thermostatically to changes in democracy. Researchers should refrain from hand-entering data as much as possible, and we offer additional suggestions for avoiding errors.

The study of public opinion in comparative context has been hampered by data that is sparse, that is, unavailable for many countries and years; incomparable, i.e., ostensibly addressing the same issue but generated by different survey items; or, most often, both. Questions of representation and of policy feedback on public opinion, for example, cannot be explored fully from a cross-national perspective without comparable time-series data for many countries that span their respective times of policy adoption. Recent works (Claassen 2019; Caughey, O'Grady, and Warshaw 2019) have introduced a latent variable approach to the study of comparative public opinion that maximizes the information gleaned from available surveys to overcome issues of sparse and incomparable data and allow comparativists to examine the dynamics of public opinion. This paper advances this field of research by presenting a new model and software for estimating latent variables of public opinion from cross-national survey data that yield superior fit and more quantities of theoretical interest than previous works allow.

Objective: This article documents wide-ranging revisions to the Standardized World Income Inequality Database (SWIID), which seeks to maximize the comparability of income inequality estimates for the broadest possible coverage of countries and years. Methods: Two k-fold cross-validations, by observation and by country, are used to evaluate the SWIID's success in predicting the Luxembourg Income Study (LIS), recognized in the field as setting the standard for comparability. Results: The cross-validations indicate that the new SWIID's estimates and their uncertainty are even more accurate than previous versions, extending its advantage in comparability over alternate income inequality datasets. Conclusion: Given its superior coverage and comparability, the SWIID remains the optimum source of data for broadly cross-national research on income inequality.

Objective. How does economic inequality shape participation in political campaigns? Previous research has found that higher inequality makes people of all incomes less likely to participate in politics, consistent with relative power theory, which holds that greater inequality enables wealthier citizens to more fully reshape the political landscape to their own advantage. Campaign activities, however, demand more time and money than previously examined forms of participation and so might better conform to the predictions of resource theory, which focuses narrowly on the ramifications of inequality for individuals’ resources. Methods. We combine individual-level data on donations, meeting attendance, and volunteer work for political campaigns with measures of state-level income inequality to construct a series of multilevel models. Results. The analyses reveal that where inequality is higher, campaign participation is lower among individuals of all incomes. Conclusion. Patterns of participation in even resource-intensive campaign activities provide support for the relative power theory. Forthcoming, Social Science Quarterly.

Do contexts of greater income inequality spur the disadvantaged to achieve a class consciousness vital to contesting the fairness of the economic system and demanding more redistribution? One prominent recent study, Newman, Johnston, and Lown (2015), argues that simple exposure to higher levels of local income inequality lead low-income people to view the United States as divided into haves and have-nots and to see themselves as among the have-nots, that is, to become more likely to achieve such a class consciousness. Here, we show that this sanguine conclusion is at best supported only in analyses of the single survey presented in that study. There is no evidence that higher levels of income inequality produce greater class consciousness among those with low incomes in other similar but neglected surveys.