Understanding how people exchange beliefs giving rise to complex attitude-identity systems is crucial for the social sciences, data science, and policymaking. Yet, many established research methods struggle to account for the ecological complexity of these processes, especially with regard to the structural architecture of attitude systems, their embedding in identity, and the challenges of comparing empirical results. ResIN (Response Item Networks), an innovative method inspired by Belief Network Analysis (BNA), seeks to address many of the limitations of traditional analytical ...
The advent of nearly global estimates of democratic mood represents a genuine cause for optimism around identifying the linkages between public opinion and democracy. This has recently been boosted by claims that novel approaches to measuring latent democratic mood with hierarchical IRT measurement models overcome cross-national differential item functioning (DIF) and, in turn, the biases from violations of scalar invariance – fundamental challenges that typically foil the comparability of country-level estimates of latent quantities. Focusing specifically on the issue of scalar...
Unlike U.S.appellate courts, scholars of the American federal judiciary typically lack ideological estimates for district court judges that are derived directly from their behavior. Rather, scholars have primarily relied upon proxy measures based upon the preferences of a judge's appointing president or those of home-state senators in the event senatorial courtesy is in effect. Nevertheless, senatorial courtesy is a norm, and norms can be broken. It remains an open question whether home-state senators genuinely constrain the president when it comes to the ideological tenor...
We introduce ResIN, a package for the R programming language designed to estimate, visualize, and analyze Response-Item Networks (ResIN ). ResIN is an increasingly popular method for modeling complex socio-political attitude systems as sparse, spatially interpretable networks. The package simplifies and unifies the underlying workflow while offering a range of convenience features, including network plotting, community detection, psychometric score extraction, bootstrap-based uncertainty estimation, and the export of ResIN objects to other statistical software environments...
Investigating attitude systems is of key interest to many social scientists. However, “classic” approaches to studying such systems like linear scaling or dimensionality reduction risk hiding useful information and may artificially narrow the scope of explanatory theories. As an alternative, scholars have recently turned to Belief Network Analysis (BNA), which formalizes mass attitudes as sets of statistically interconnected nodes. However, BNA inherits many of the assumptions typical of latent variable methods which can preclude explorations of more complex phenomena, such as ...
Public opinion research has made tremendous progress in identifying the conditions under which individual- and group-level factors induce citizens to form coherent political attitudes, yet comparatively little attention has been given to the role of national political context for belief system coherence. By modeling political beliefs as dedicated statistical networks based on nationally representative surveys covering 38 European countries between 2002 and 2020, the present article shows that national-level belief systems vary substantially and systematically...
Belief network analysis (BNA) has enabled major advances in the study of belief systems, capturing Converse’s understanding of the interdependence among multiple beliefs (i.e., constraint) more intuitively than conventional statistics. However, BNA models struggle with representing political divisions that follow a spatial logic, such as the “left-right” or “liberal-conservative” ideological divide. We argue that Response Item Networks (ResINs)are advantageous for such analyses as they model belief systems in a latent ideological space. In addition to retaining many desirable properties...
Public opinion research has made tremendous progress in identifying the conditions under which individual- and group-level factors induce citizens to form coherent political attitudes, yet comparatively little attention has been given to the role of national political context for belief system coherence. By modeling political beliefs as dedicated statistical networks based on nationally representative surveys covering 38 European countries between 2002 and 2020, the present article shows that national-level belief systems vary substantially and systematically...
The social sciences heavily depend on the measurement of abstract constructs for quantifying effects, identifying association between variables, and testing hypotheses. In data science, constructs are also often used for forecasting, and, thanks to the recent big data revolution, they promise to enhance their accuracy by leveraging the constantly increasing stream of digital information around us. However, the possibility of optimizing various social indicators implicitly hinges on our ability to reliably reduce complex and abstract constructs (such as life satisfaction or social trust) into numeric measures...
This article undertakes a comprehensive investigation into several common critiques of career politicians. Career politicians are said to be self‐serving, active and assertive when it suits their career interests, and much more interested in attaining higher offices than in serving as constituency‐oriented MPs. Yet, empirical investigations of their alleged behaviors are few, and the results are patchy and mixed. Focusing on the United Kingdom case and using a multi‐dimensional conceptualization that accords with academic and popular understandings of career politicians, the article draws on uniquely rich attitudinal and longitudinal behavioral data covering the first large generational wave of career politicians to be elected to parliament in the early 1970s...