This article examines the information sharing behavior of U.S. politicians and the mass public by mapping the ideological sharing space of political news on social media. As data, we use the near-universal currency of online information exchange: web links. We introduce a methodological approach and software to unify the measurement of ideology across social media platforms by using sharing data to jointly estimate the ideology of news media organizations, politicians, and the mass public. Empirically, we show that (1) politicians who share ideologically polarized content share, by far, the most political news and commentary and (2) that the less competitive elections are, the more likely politicians are to share polarized information. These results demonstrate that news and commentary shared by politicians come from a highly unrepresentative set of ideologically extreme legislators and that decreases in election pressures (e.g., by gerrymandering) may encourage polarized sharing behavior.

In this article, we explore the rhetorical space structuring the debates in the United Nations General Assembly's (UNGA) Committee on Disarmament and International Security. To this end, we unfold states' speeches by combining three established methods. First, we estimate terms' relevance for latent topics structuring the debates with structural topic modeling. Second, we estimate topic-specific positions based on the Wordfish algorithm. Third, we map these positions onto a lower-dimensional rhetorical space using principal component analysis. We identify two latent conflicts. First, a debate over conventional weapons with states emphasizing security interests on the one end and humanitarian interests on the other. Second, a conflict over weapons of mass destruction that divides defenders and challengers of the status quo.

Lobbying expenditures are widely used as a proxy variable for measuring lobbying activity. However, the validity of this approach has rarely been examined and existing justifications do not account for heterogeneity in expenditure formats across types of lobbyists. I address the question using unique lobbying disclosure data from Wisconsin, where lobbying organizations report both expenditures on lobbying-related activities and lobbyists’ hours worked. Strong overall correlations between changes in expenditures and hours worked within organization–lobbyist dyads indicate that lobbying expenditures can serve as a reasonable proxy. However, caution is warranted due to substantial heterogeneity, with contract lobbyist relationships exhibiting weaker correlations than in-house relationships. I conclude by providing suggestions to improve empirical analyses that rely on lobbying expenditures.

Numerous differences exist between and within research projects related to assessment and operationalization of potentially traumatic events (PTEs) for youth, especially when measuring polyvictimization. However, few studies have systematically examined how polyvictimization measurement differences influence PTE’s relation to functioning. This study sought to address these knowledge gaps by conducting a secondary data multiverse replication (SDMR) to systematically (re)evaluate PTE polyvictimization measurement approaches. Participants included 3297 adolescents (Mage = 14.63; 50.59% female; 65.15% white) from the National Survey of Adolescents-Replication study who completed a structured interview on PTE exposure and emotional and behavioral health (i.e., posttraumatic stress and major depressive disorder, drug and alcohol use, and delinquency). Results indicated that PTE operationalizations using a count variable tended to demonstrate better model performance and prediction of youth at-risk of emotional and behavioral health challenges, compared to models using a binary (yes/no) PTE operationalization. Differences in model performance and prediction were less distinct between models examining multiple forms of a single type of PTE (e.g., maltreatment, community violence), compared to models examining multiple PTE types. These findings emphasize the importance of using multidimensional approaches to PTE operationalization and the need for more multiverse analyses to improve PTE evidence-based assessment.

Political polarization has become an increasingly salient issue worldwide, but a systematic examination of the variation and sources of mass polarization across countries is limited by current measurement methods. This work proposes a nonparametric, entropy-based measure of mass political polarization. It exploits the specific structure of ordinal distributions in public opinion data, makes no prior assumptions about the form and spacing of the data, and can still draw reliable measures of issue-based polarization. We demonstrate the theoretical and practical superiority of the measure with analytical comparisons and simulations. We then apply the proposed measure to questions about mass polarization in the USA, the relationship between radical parties and polarization in Europe, and cross-country trends in affective and ideological polarization.

This paper deals with a construction, which we dub Non-Agreeing Degree (NAD) constructions, with the distinguishing property that the agreement pattern between subjects and degree predicates is optionally disrupted, even in languages (like Spanish) where verbs commonly agree with their subjects. We show that the agreeing versus non-agreeing alternation comes with important semantic differences for the interpretation of the degree construction. We provide a first systematic description of this type of constructions and postulate a formal syntactic and semantic analysis. We argue that NAD constructions are characterized by degree predicates that introduce a non-conventional nominal scale and by subjects that are interpreted as equally non-conventional units of measurement. We postulate an intensionalization process on the subject of NAD constructions, which we capture via a general nominalization function that allows a default as well as an ordinary agreement pattern between subject and copula.

How do international crises unfold? We conceptualize international relations as a strategic chess game between adversaries and develop a systematic way to measure pieces, moves, and gambits accurately and consistently over a hundred years of history. We introduce a new ontology and dataset of international events called ICBe based on a very high-quality corpus of narratives from the International Crisis Behavior (ICB) Project. We demonstrate that ICBe has higher coverage, recall, and precision than existing state of the art datasets and conduct two detailed case studies of the Cuban Missile Crisis (1962) and the Crimea-Donbas Crisis (2014). We further introduce two new event visualizations (event iconography and crisis maps), an automated benchmark for measuring event recall using natural language processing (synthetic narratives), and an ontology reconstruction task for objectively measuring event precision. We make the data, supplementary appendix, replication material, and visualizations of every historical episode available at a companion website crisisevents.org.

Theoretical expectations regarding communication patterns between legislators and outside agents, such as lobbyists, agency officials, or policy experts, often depend on the relationship between legislators’ and agents’ preferences. However, legislators and nonelected outside agents evaluate the merits of policies using distinct criteria and considerations. We develop a measurement method that flexibly estimates the policy preferences for a class of outside agents—witnesses in committee hearings—separate from that of legislators’ and compute their preference distance across the two dimensions. In our application to Medicare hearings, we find that legislators in the U.S. Congress heavily condition their questioning of witnesses on preference distance, showing that legislators tend to seek policy information from like-minded experts in committee hearings. We do not find this result using a conventional measurement placing both actors on one dimension. The contrast in results lends support for the construct validity of our proposed preference measures.

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.