Since the first Trump administration, historically marginalized groups in the United States have been subjected to greater instances of bigotry and discrimination due to conservative influence on sociopolitical institutions. These actions suggest a shift in the “Overton Window,” whereby policy preferences previously deemed “unacceptable” are given consideration in the mainstream, especially by conservative policy actors. “Project 2025” is a comprehensive plan to restructure the federal government according to conservative dictates in the second Trump administration. This article is an examination of how higher education may be impacted by this plan, especially as it relates to LGBTQ+1 faculty, administration, staff, and students.

In this article, we assess the availability of reproduction archives in political science. By “reproduction archive,” we mean the data and code supporting quantitative research articles that allows others to reproduce the computations described in the published article. We collect a random sample of quantitative research articles published in political science from 1995 to 2022. We find that—even in 2022—most quantitative research articles do not point to a reproduction archive. However, practices are improving. In 2014, when the DA-RT symposium was published in PS: Political Science and Politics, about 12% of quantitative research articles point to the data and code. Eight years later, in 2022, that has increased to 31%. This underscores a massive shift in norms, requirements, and infrastructure. Still, only a minority of articles share the supporting data and code. In 2014, Lupia and Alter wrote, “Today, information on the data production and analytic decisions that underlie many published works in political science is unavailable.” They could write the same today; much work remains to be done.

Taiwan’s achievement in passing a marriage-equality law in 2019 and the democratic backlash against LGBTQ+ rights deserve scholarly attention in Asia and beyond. Specifically, Taiwan’s road to marriage equality led to these empirical puzzles: What explains the conservative shift in Taiwan’s public perceptions toward LGBTQ+ rights? How would the backlash against LGBTQ+ rights impact Taiwan’s democracy? What does Taiwan’s experience inform us about norm localization and LGBTQ+ politics in Asia and beyond?

The strategic framing of the Christian right—that is, the symbolic use of family and its localization of conservative values using Confucian norms—enabled them to couch their religious beliefs and facilitate collective action among different groups. This study offers a culture-based explanation of how the Christian right successfully established a single-issue coalition against LGBTQ+ rights. The article is organized as follows. First, it engages current literature on discourse analysis, norms contestation, and contentious politics. Second, the study proposes a two-part framework for understanding how the Christian right effectively constructs their conservative claims to gain public support. A comparative analysis of the discourse from the conservative and progressive sides sheds light on how their narratives shaped the marriage-equality debate. Third, it addresses how this countermovement impacts Taiwan’s democracy and human rights.

This article examines the effectiveness of LGBTQ groups in Congress by looking at voting in favor of bills concerning queer rights. I find that the effect of donations is present in the early period of queer bills before Congress but disappears in bills post-2018. Instead, party is the dominant explanation for votes on bills. This has implications for the strategies that should be employed by LGBTQ+ interests at the national level and implications for how political science should examine the interactions between interest groups and new venues of change.

Artificial intelligence in higher education has expanded worldwide with the growth of AI technologies. The emergent applications of artificial intelligence in higher education (AIEd) in course preparation, delivery, and administration as well as in learning assistants and prediction for the sake of learners are widely considered important innovations that can change education worldwide. The Armenian case was examined via a survey that was conducted at the country’s leading universities to investigate whether and how faculty use AIEd. Although the results indicate that many Armenian teaching faculty use AIEd in narrow capacities and acknowledge the potential usefulness of AIEd in the practical administration of Armenia’s higher education, the use of AIEd is not deep.

We consider how LGBT+ legal rights frameworks, broadly construed, can be used to bolster support within the general public for transgender subgroup rights. Our research is informed by theoretical perspectives on appeals to superordinate identities to reduce prejudice. Based on a survey experiment in the United States, we find that framing a salient transgender advocacy issue—transgender participation in sports—within a broader LGBT+ legal rights framework increases public support for transgender inclusion in sports. There is a nearly 10 percentage-point increase in support, including among partisan Republicans, when transgender rights in sports are preceded by priming and framing around the more general LGBT+ rights struggle. Our results underscore the importance of broader LGBT+ rights advocacy to public acceptance of the transgender community.

Conducting elite interviews presents well-documented challenges, often linked to dynamics that are influenced by researchers’ status. This aspect of positionality is sometimes characterized as “insider” or “outsider” status, but scholars have noted the lack of nuance in this rigid binary. Drawing on experiences during interviews with policy elites—primarily in England—this article describes the author’s “in-betweener” status and reviews four methodological considerations from this perspective, highlighting the challenges and opportunities associated with different points on the insider–outsider spectrum. These observations are meant to stimulate reflexivity among researchers regardless of their status.

“Gender ideology” rhetoric has diffused globally. Mobilized by a coalition of conservative actors, this discursive innovation helps to fuel the election of far-right politicians who scapegoat LGBTQ people, migrants, racial and ethnic minorities, and women as responsible for economic downturns as well as social and political disorder. This essay outlines the history and current landscape of gender ideology for political scientists and situates it in relation to the rise of far-right and authoritarian regimes globally. It builds on these political trends by concluding with a research agenda for scholars of LGBTQ politics to consider moving forward.

Drag has a long history in the LGBTQ community as a means of political engagement, activism, protest, and community building. Today, drag is popular in the LGBTQ community and in the rest of society. At the same time, it is routinely a target of conservative backlash against the LGBTQ community. Despite drag’s inherently political nature, political science has failed to engage substantially with the influence of drag. This article offers a justification and research agenda to bring drag into the mainstream of political science.

This is the expanded written version of the James Madison Lecture delivered on September 6, 2024, at the APSA Annual Meeting in Philadelphia, PA. I grapple with the pressing question before us as social scientists and as citizens: How and why have US politics and governance arrived at the present juncture where long-standing constitutional practices and democratically responsive governance are very much at stake? My answer focuses on what I see as the prime driver of the current crisis: the recent radicalization of the Republican Party and its allies, as they have pursued two forms and phases of antidemocratic politics. The first version involves maximum use of legal hardball steps that stretch existing laws and rules to disadvantage partisan opponents (I also call this approach “McConnellism” in honor of its chief practitioner, outgoing GOP Senate Leader Mitch McConnell of Kentucky). The second approach targets political competitors and government operations with extralegal harassment, threats of violence, and even actual violence. Drawing on my own research with many collaborators, as well as from many excellent studies by colleagues in political science and beyond, I will dissect the elite and popular roots of recent Republican embrace of both forms of antidemocratic politics.

Former president Trump has maintained broad support despite falsely contending that he was the victim of electoral fraud, also known as the “big lie.” We consider both the antecedents of this phenomenon and its consequences. We propose that Trump supporters’ already established deep personal alignment—identity fusion—with their leader predisposed them to believe the lie. Accepting it then set the foundation for other identity-protecting beliefs and attitudes. Using a three-wave panel of Trump supporters, we found that the more fused they were before the 2020 election, the stronger their belief in the big lie grew between 2021 and 2024. Accepting the big lie helped solidify fusion with Trump and had consequences for related attitudes. Belief in the big lie predicted downplaying the criminal charges against Trump and supporting his antidemocratic policy agenda. Fueled by and fueling further fusion, belief in the big lie is a primary component of a larger narrative that emboldens Trump and justifies antidemocratic behavior.

Today, few political news outlets receive universally favorable evaluations from the American public. In retaining broad public approval, local media remain a notable exception that is important to understand. We consider the durability of local news trust to criticism from politicians, focusing on Republican elites because they generally are more willing to attack the media than Democrats. In a survey experiment, we find that exposure to a Republican politician’s attack on a local newspaper dramatically reduces the public’s trust in and intent to use local news. This attack is particularly effective among Republicans, although it also leads Democrats and Independents to negatively shift their views of the local newspaper. Among those exposed to elite criticism of local news, overall trust and partisan divides between Republicans and Democrats resemble those for national media. This shows that the credibility of local news depends on the absence of elite criticism rather than resilience to it.

Many important questions in political science require the use of human-coded data or information that has been systematically ordered and quantified by a human being from qualitative sources. This article discusses challenges and recent innovations in collecting and documenting human-coded data. We review five datasets produced within the past 10 years and also reflect on our experiences in collecting a quarterly dataset that tracked state responses to the COVID-19 pandemic. We argue that scholars can deliberately produce and publish theoretically grounded human-coded data in an accessible format that promotes transparency, traceability, and readability. We highlight several ways that scholars are already doing this, including narratives, source lists, and coding justifications that enhance the quality of their human-coded datasets. We also discuss common issues during coding and how technological innovation through interactive web-based platforms can improve the documentation of coding decisions.

This article investigates the impact of ChatGPT on student writing in the context of Model United Nations position papers, which require extensive research and concise articulation of policies on international issues. By comparing student-written papers and ChatGPT-generated papers, we find that whereas AI-generated papers received higher evaluations overall, award-winning student papers outperformed AI-generated papers. Furthermore, the quality of AI-generated writing is shown to depend on human input, emphasizing the importance of a human-centered approach to AI in education.

The intersection of conflict research and research ethics is already a complex and fraught one, particularly in exchanges between researchers from the Global North and researched communities from the Global South. There are many examples (and years) of exploitation, fraud, and violence in these exchanges, and more recent scholarship on fieldwork ethics has established new norms of reciprocal exchange rather than exploitation in these relationships. However, the outbreak of the COVID-19 pandemic, asymmetric access to health care, and global vaccine inequality has added yet another layer of complexity here. How do we continue move forward with the push to make our research exchanges ethical while dealing with the additional complexity of the pandemic? In this article, I reflect on the ethics of these exchanges and concerns around security for interlocutors in replacing in person fieldwork with virtual fieldwork, drawing from examples of my own doctoral dissertation research in the Pacific region of Colombia, which was interrupted by the outbreak of COVID-19. In this article, I describe how a turn to the digital archives helped mitigate additional ethical and security concerns that arose as a result of the pandemic.

Using a forecasting model based on economic pessimism and recognizing the difficulties of making such a forecast in such atypical times, the forecasting model predicts a narrow loss for the incumbent presidential party and a loss of 12 seats in the House of Representatives. Even with the unusual nature of politics in the United States over the past decade, this model does a good job of predicting election outcomes. The more pessimistic people are, the worse the incumbent party does in presidential and House elections. Moreover, the power of incumbency shows strongly.

In this article, we build a model to predict the state-level results of the 2024 election. We do so by using both polling from similar points in past election cycles and the results of the previous election. Notably, we update our model over time, and the coefficients of the two variables change as a result: the model puts more weight on polling as the election gets closer. As of September 1, 2024, we find that Kamala Harris is a narrow favorite to win the 2024 election, with a 57% chance of doing so. Currently, the model predicts she will win 289 electoral votes to Trump’s 249. However, there remains significant uncertainty, and the model will continue to be updated as the election nears.

This article considers both presidential approval and party brand differentials, as measured by the generic ballot, to forecast the 2024 US presidential and congressional elections. Although both variables are leveraged to forecast collective partisan election outcomes, we consider the variables together as distinct determinants of partisan fortunes at both the executive and legislative levels. First, using a novel time series of mass national opinion since 1937, we show that presidential approval and generic brands are distinct conceptual and empirical measures of mass public assessments of collective institutions. Second, in a series of fully specified models validated with out-of-sample predictions, we show that presidential approval is the main predictor of presidential elections, yet, perhaps surprisingly, the vast bulk of the incumbent party’s performance in congressional elections is explained by partisan brands. Lastly, we forecast the 2024 U.S. national elections and find that Republicans are well positioned to win back the White House this November. By contrast, our model forecasts control of both chambers of the US Congress to be essentially a tied contest.

Donald Trump’s bid for the 2024 Republican presidential nomination is unique in that no former president since Theodore Roosevelt in 1912 has sought the nomination of their political party, nor has a candidate sought the nomination while facing multiple criminal indictments. With data from previous nomination cycles, we use presidential nominations from 1980 to 2020 to create a forecast for the 2024 Republican primaries. The variables in the equations consist of data from the pre-primary period (e.g., money raised, cash reserves, elite endorsements, and polling results) and a second model with results of the Iowa caucuses and the New Hampshire primary to forecast the remaining primary vote. The models accurately predict Trump’s victory despite the unique nature of his candidacy.

Voter turnout is a crucial indicator of democratic health, yet forecasting turnout remains an understudied area in political science. This article presents two pioneering models for predicting US presidential election turnout: the national and the state model. The national one, using data from 1868 from 2020, employs lagged turnout as its sole predictor. The state model, covering 1984 to 2020, incorporates demographic and institutional variables to forecast state-level participation. The national predicts 65.3% turnout for 2024, whereas the state model forecasts increased turnout in 41 states compared to 2020. The models’ ability to generate early predictions offers valuable lead time for planning and resource allocation, which has implications for election administrators and political campaigns, as well as for the vibrancy of civic engagement in America.