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In the 2023 ASA presidential address, Prudence Carter delves into the landscape of U.S. society, tracing some of its historical progress and confronting contemporary social, economic, educational, and political challenges. Central to her argument is an exploration of the concept of "unrealized integration" and how it has hindered the nation's march toward an inclusive, multiracial democracy. Carter describes and characterizes the current state of integration within education and society. Despite the widespread rhetoric of diversity in our organizations and institutions, she critiques its shallow application, exposing diversity's inability to rectify imbalances of power- and resource-sharing. Incorporating the idea of "tipping points," she discusses how civil rights movements, despite expanding representation and opportunity, have faced recurrent waves of political backlash and reversals. She contends that an erosion of social progress occurs when there is an imbalance in the pursuit of distributional equality (concerning material resources) and relational equality (involving social and cultural dynamics and processes that shape well-being). Additionally, she identifies three other crucial areas that warrant focus to pave the path toward realized integration within education and society. In a forward-looking call to arms, Carter underscores the imperative for sociologists to transcend epistemological and methodological boundaries; and she advocates for robust collaborations across the social sciences and humanities to harness the collective power of knowledge-generation and solution-building for pressing societal issues. [ABSTRACT FROM AUTHOR]

Rising inequalities in rich countries have led to concerns that the economic ladder is getting harder to climb. Yet, research on trends in intergenerational income mobility finds conflicting results. To better understand this variation, we adopt a multiverse approach that estimates trends over 82,944 different definitions of income mobility, varying how and for whom income is measured. Our analysis draws on comprehensive register data for Swedish cohorts born 1958 to 1977 and their parents. We find that income mobility has declined, but for reasons neglected by previous research: improved gender equality in the labor market raises intergenerational persistence in women's earnings and the household incomes of both men and women. Dominant theories that focus on childhood investments have blinded researchers to this development. Methodologically, we show how multiverse analysis can be used with abduction—inference to the best explanation—to improve theory-building in social science. [ABSTRACT FROM AUTHOR]

Conspiracies are consequential and social, yet online conspiracy groups that consist of individuals (and bots) seeking to explain events or a system have been neglected in sociology. We extract conspiracy talk about the COVID-19 pandemic on Twitter and use the biterm topic model (BTM) to provide a descriptive baseline for the discursive and social structure of online conspiracy groups. We find that individuals enter these communities through a gateway conspiracy theory before proceeding to extreme theories, and humans adopt more diverse conspiracy theories than do bots. Event-history analyses show that individuals tweet new conspiracy theories, and tweet inconsistent theories simultaneously, when they face a threat posed by a rising COVID-19 case rate and receive attention from others via retweets. By contrast, bots are less responsive to rising case rates, but they are more consistent, as they mainly tweet about how COVID-19 was deliberately created by sinister agents. These findings suggest human beings are bricoleurs who use conspiracy theories to make sense of COVID-19, whereas bots are designed to create moral panic. Our findings suggest that conspiracy talk by individuals is defensive in nature, whereas bots engage in offense. [ABSTRACT FROM AUTHOR]

Legitimacy is widely invoked as a condition, cause, and outcome of other social phenomena, yet measuring legitimacy is a persistent challenge. In this article, I synthesize existing approaches to conceptualizing legitimacy across the social sciences to identify widely agreed upon definitional properties. I then build on these points of consensus to develop a generalizable approach to operationalization. Legitimacy implies specific relationships among three empirical elements: an object of legitimacy, an audience that confers legitimacy, and a relationship between the two. Together, these empirical elements constitute a dyad (i.e., a single unit consisting of two nodes and a tie). I identify three necessary conditions for legitimacy— expectations, assent, and conformity —that specify how elements of the dyad interact. I detail how these conditions can be used to empirically establish legitimacy (and illegitimacy), distinguishing it from dissimilar phenomena that often appear similar empirically. Followed to its logical conclusion, this operationalization has novel implications for understanding the effects of legitimacy. I discuss these implications, and how they inform debates over the relevance of legitimacy as an explanation for socially significant outcomes. [ABSTRACT FROM AUTHOR]

We make only one point in this article. Every quantitative study must be able to answer the question: what is your estimand? The estimand is the target quantity—the purpose of the statistical analysis. Much attention is already placed on how to do estimation; a similar degree of care should be given to defining the thing we are estimating. We advocate that authors state the central quantity of each analysis—the theoretical estimand—in precise terms that exist outside of any statistical model. In our framework, researchers do three things: (1) set a theoretical estimand, clearly connecting this quantity to theory; (2) link to an empirical estimand, which is informative about the theoretical estimand under some identification assumptions; and (3) learn from data. Adding precise estimands to research practice expands the space of theoretical questions, clarifies how evidence can speak to those questions, and unlocks new tools for estimation. By grounding all three steps in a precise statement of the target quantity, our framework connects statistical evidence to theory. [ABSTRACT FROM AUTHOR]

In light of ongoing concerns about the relevance of scholarly activities, we ask, what are public ideas and how do they come to be? More specifically, how do journalists and other mediators between the academy and the public use social science ideas? How do the various uses of these ideas develop over time and shape the public careers of these ideas? How do these processes help us understand public ideas and identify their various types? In addressing these questions, we make the case for a sociology of public social science. Using data from newspaper articles that engage with seven of the most publicly prominent social science ideas over the past 30 years, we make three contributions. First, we advance a pragmatic, cultural approach to understanding public ideas, one that emphasizes fit-making processes and applicative flexibility. Second, we define public ideas: social science ideas become public ideas when they are used as objects of interest (being the news), are used as interpretants (making sense of the news), and ebb and flow between these uses as part of an unfolding career. Third, we construct a typology of public ideas that provides an architecture for future research on public social science. [ABSTRACT FROM AUTHOR]

Drawing on Bayesian probability theory, we propose a generalization of affect control theory (BayesACT) that better accounts for the dynamic fluctuation of identity meanings for self and other during interactions, elucidates how people infer and adjust meanings through social experience, and shows how stable patterns of interaction can emerge from individuals’ uncertain perceptions of identities. Using simulations, we illustrate how this generalization offers a resolution to several issues of theoretical significance within sociology and social psychology by balancing cultural consensus with individual deviations from shared meanings, balancing meaning verification with the learning processes reflective of change, and accounting for noise in communicating identity. We also show how the model speaks to debates about core features of the self, which can be understood as stable and yet malleable, coherent and yet composed of multiple identities that may carry competing meanings. We discuss applications of the model in different areas of sociology, implications for understanding identity and social interaction, as well as the theoretical grounding of computational models of social behavior. [ABSTRACT FROM AUTHOR]