To investigate general patterns in news information in the United States, we combine a protocol for identifying major political news stories, 11 monthly surveys with 15,000 participants, and a model of news discernment. When confronted with a true and a fake news story, 47 percent of subjects confidently choose the true story, 3 percent confidently choose the fake story, and the remaining half are uncertain. Socioeconomic differences are associated with large variations in the probability of selecting the true news story. Partisan congruence between an individual and a news story matters, but its impact is up to an order of magnitude smaller.

Research shows that sexist attitudes are deeply ingrained, with adverse consequences in the socioeconomic and political sphere. We argue that parental leave for fathers—a policy reform that disrupts traditional gender roles and promotes less stereotypical ones—has the power to decrease attitudinal gender bias. Contrasting the attitudes of new parents who were (and were not) directly affected by a real-world policy reform that tripled the amount of fathers’ leave, we provide causal evidence that the reform increased gender-egalitarian views in the socioeconomic and political domains among mothers and fathers, and raised support for pro-female policies that potentially displace men among mothers. In contrast, informational, indirect exposure to the reform among the general public produced no attitudinal change. These results show that direct exposure to progressive social policy can weaken sexist attitudes, providing governments with a practical and effective tool to reduce harmful biases.

Competition between social units has long been central to sociological theories of change. Understanding it has become particularly important in the sociology of religion with the theory of religious economies, a market model of religious change. Existing empirical tests of the theory are limited by (1) ambiguity regarding which religious groups are expected to compete with which other groups, and/or (2) a neglect of the local level (competition among congregations). Using an original compilation of the life histories of religious congregations in Manhattan from 1949 to 1999, I conduct event-history analyses that avoid those limitations. The chief results are the following: (1) the more congregations there were near a given congregation that were theologically dissimilar to that congregation, the less likely that congregation was to advertise; (2) when there was an increase over time in the number of nearby congregations that were theologically similar to the focal congregation, that congregation became more likely to advertise; and (3) when there was an increase over time in the number of nearby congregations that were theologically dissimilar to the focal congregation, that congregation became less likely to advertise. Implications for the study of religion include modifications of religious-economies theory; broader implications speak to understanding the social units that compete and what drives competition.

Federal administrative data, such as tax data, are invaluable for research, but because of privacy concerns, access to these data is typically limited to select agencies and a few individuals. An alternative to sharing microlevel data is to allow individuals to query statistics without directly accessing the confidential data. This article studies the feasibility of using differentially private (DP) methods to make certain queries while preserving privacy. We also include new methodological adaptations to existing DP regression methods for using new data types and returning standard error estimates. We define feasibility as the impact of DP methods on analyses for making public policy decisions and the queries accuracy according to several utility metrics. We evaluate the methods using Internal Revenue Service data and public-use Current Population Survey data and identify how specific data features might challenge some of these methods. Our findings show that DP methods are feasible for simple, univariate statistics but struggle to produce accurate regression estimates and confidence intervals. To the best of our knowledge, this is the first comprehensive statistical study of DP regression methodology on real, complex datasets, and the findings have significant implications for the direction of a growing research field and public policy. Supplementary materials for this article are available online.

Payoff-biased cultural learning has been extensively discussed in the literature on cultural evolution, but where do payoff currencies come from in the first place? Are they products of genetic or cultural evolution? Here we present a simulation model to explore the possibility of novel payoff currencies emerging through a process of theory construction, where agents come up with “channels” via which different cultural traits contribute to some ultimate payoff and use such “channels” as intermediate payoff currencies to make trait-updating decisions. We show that theory-building as a strategy is mostly favored when the noise associated with the ultimate-level payoff is high, selective pressures are strong, and the probability of arriving at the right theory is high. This approach provides insights into both the emergence of payoff currencies and the role of cognition for causal model building. We close by discussing the implications of our model for the broader question of causal learning in social contexts.

Digitization has changed many aspects of scholarly research. While many transformations are obvious, some have remained under-remarked and under-theorized. One such under-remarked transformation is the availability of digitized historical newspapers. Millions of pages of newspapers from the eighteenth century onward are available for scholars and the general public to peruse. Many members of the general public use these sources for genealogical research. Meanwhile, scholars have used them for everything from a few citations to new types of digital humanities projects. To name a couple of examples, Kristi Palmer has traced the emergence of the term “Hoosier” for Indiana. An interdisciplinary team has created a database of newspaper ads around fugitive slaves in the United States. One of the contributors to this AHR History Lab forum, Ryan Cordell, has created an Oceanic Exchanges project to explore transatlantic reprinting. Beyond specific projects, scholars’ use of newspapers as a source has increased significantly in myriad ways. Initiatives have sprung up to encourage more use of newspapers, such as the Black Press Research Collective. In 2013, Ian Milligan found that dissertations cited newspapers like Toronto Star ten times as often after the newspaper had been digitized. Some early career researchers are making digitized newspapers a central feature of their work. One contributor to this History Lab forum, Zoe LeBlanc, completed the first digital history dissertation at Vanderbilt University in 2019, using digitized records to trace media use in the Middle East. Meanwhile, Kira Thurman’s multi-award-winning first book started with digitized American and Austrian newspapers to find Black musicians in Germany, as German newspapers had not been digitized to the same extent. She then moved to archival sources, memoirs, musical scores, and more. COVID-19 supercharged that trend for basically everyone working on the eighteenth century onward.

Scholarly citation represents one of the most common and essential elements of psychological science, from publishing research, to writing grant proposals, to presenting research at academic conferences. However, when authors mischaracterize prior research findings in their studies, such instances of miscitation call into question the reliability and credibility of scholarship within psychological science and can harm theory development, evidence-based practices, knowledge growth, and public trust in psychology as a legitimate science. Despite these implications, almost no research has considered the prevalence of miscitation in the psychological literature. In the largest study to date, we compared the accuracy of 3,347 citing claims to original findings across 89 articles in eight of top psychology journals. Results indicated that, although most (81.2%) citations were accurate, roughly 19% of citing claims either failed to include important nuances of results (9.3%) or completely mischaracterized findings from prior research altogether (9.5%). Moreover, the degree of miscitation did not depend on the number of authors on an article or the seniority of the first authors. Overall, results indicate that approximately one in every 10 citations completely mischaracterizes prior research in leading psychology journals. We offer five recommendations to help authors ensure that they cite prior research accurately. (PsycInfo Database Record (c) 2024 APA, all rights reserved)