Whereas significant attention has been devoted to online/blended teaching and related tools, open GenAI chatbots and large language models and writing programs have received comparatively less attention as instruments that impact our teaching and assessment methods. The pedagogies of political science and international relations somehow trail behind in understanding and addressing them. For those who are teaching these subjects, it is of great importance to come to terms with AI and its impact on how we should assess students. This article describes an eight-week laboratory during which we experimented with and discussed ChatGPT’s utilizations with our students. The goal of the laboratory was to revise which type of learning objectives our teaching should have and which type of assessment methods are best suited for an environment in which GenAI is present and used regularly. Should we ban it or should we instead focus on teaching students how to use it responsibly and ethically, as well as developing a shared understanding of what GenAI is good for (if anything at all)? Consequently, which learning objectives and assessment methods should we adopt?

The rise of populism as a global phenomenon has captured the attention of scholars and raised concerns about its impact on democracy. Thanks to a growing academic consensus around an ideational definition of populism, one can observe the generation of important cumulative knowledge on the relationship between populism and democracy. Political science has been at the forefront of this development, and this symposium seeks to both offer state-of-the art information on this topic and discuss blind spots that future studies should try to address.

Populism’s effects on democracy after populists gain control of government (hereafter, populist incumbents) are some of the best theorized and documented consequences. The argument that populist incumbents threaten institutions of democratic contestation—and, less frequently, that they correct some aspects of political participation and representation—has been made from multiple approaches.1 Scholars and commentators often cite specific cases of populists harming democracy and, since 2016, several large-N studies have confirmed their negative impact. Specifically, studies repeatedly show the harmful effects of populist incumbents on civil liberties, including media freedom, horizontal accountability, and electoral integrity in both electoral and liberal democracies. Research has been less consistent in showing the positive consequences of populist incumbents, especially for democratic representation and political participation.

What undergirds the association between religious and political conservatism and “group-serving pronatalism”; that is, support for childbearing to advance social or political goals rather than for personal fulfillment? Although recent research suggests that Christian nationalism—reflecting a desire to formally privilege conservative Christian values and identity—strongly accounts for the link, previous studies have not inquired about specific group-serving reasons to have children. Analyses of nationally representative data affirm Christian nationalism (measured in two ways) as the strongest predictor of support for group-serving pronatalism; specifically, support for having children to reverse the nation’s declining fertility, perpetuate one’s religious or racial heritage, and secure influence for one’s political group. These associations are weakly or inconsistently moderated by indicators of traditionalism, conservatism, and race. Findings affirm support for having children to advance national, religious, racial, or political goals corresponds strongly with a desire to privilege a Christian national identity and social order.

The Indigenous data sovereignty movement has arisen out of the ambition of Indigenous peoples to benefit from data-informed policy while preventing extractive and harmful research practices by external governments or researchers. Tribes exercise the sovereign authority to choose whether and when to share data with researchers and institutions outside their communities. To provide insight into how Indigenous peoples feel about data sharing, we document meaningful variation in a unique, nationwide survey of Native Americans. We find that respondents support their tribes in sharing data for economic benefit and that those who vote in tribal elections are particularly supportive. As tribal leaders, Native communities, and external research partners address potentially harmful data gaps and build Indigenous data resources, our findings suggest the importance of carefully considering and communicating the purpose of data collection and sharing. Broad benefit to Indigenous peoples’ economic well-being is one factor that likely increases support for data sharing.

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.

Giving money to candidates is an important but unequal form of political voice. Among those Americans worst represented as campaign contributors are Black women and Latinas. Although inequalities in income and wealth fuel inequalities in campaign contributions, resources are an incomplete explanation. This study investigates, for Black women and Latinas, whether their views on donations to candidates differ from their views on other forms of civic and political engagement. The results, including the absence of a shared norm about giving to candidates, illuminate the challenges and opportunities of mobilizing a more representative group of campaign contributors.

The conflict over abortion in the United States shows no sign of abatement. Both supporters and opponents of abortion rights have mobilized movements, engaged in collective action, suffered defeats and won victories, and survived over many decades. To understand how the current battle is likely to progress, we need to examine the movement/countermovement dynamics that drive the mobilization and outcomes of the opposing movements (Meyer and Staggenborg 1996). This article demonstrates how ongoing mobilization is fueled by the strategies and tactics of each side, which are strongly influenced by the actions of their opponents.

Latin America historically has had some of the strictest abortion laws in the world, making unsafe procedures a main cause of mortality among women and girls. However, in the context of the Green Wave, three countries recently have amply decriminalized access to abortion: Mexico (2021, 2023), Colombia (2022), and Argentina (2020) (Uruguay did so in 2012). The recent wave of decriminalization is the culmination of larger, historical processes that involved the gradual judicialization of reproductive rights in the region. Courts have been a central part of the story. In these three cases, arguments advanced by state and nonstate actors in favor of decriminalization significantly built on jurisprudence developed over many years. The process of abortion decriminalization has been partly a tale of gradual judicialization.

The Southern Cone has been at the forefront of the fight for abortion rights in Latin America. Due to the legacies of Hispanic legal traditions and the overwhelming political influence of the Catholic Church, the region historically has been known for its restrictive policies on abortion and reproductive rights more broadly.1 However, in the past 15 years, Southern Cone countries began to challenge those restrictions and embarked on a feminist revolution that led to what is now widely known as the “Green Wave” because of the color embraced by abortion-rights activists. Uruguay began this trend of legalizing abortion on demand in 2012, followed by Argentina in 2020. Chile experienced a moderate reform in 2017 when it moved from a total ban to a system of exceptions. Feminists have been trying ever since to pass abortion on demand through both legislative and constitutional reforms, which have not yet yielded the expected results.

Across Latin American countries, there is remarkable heterogeneity in abortion legislation, ranging from full prohibition to legal elective abortion.1 However, abortion policy does not seem to clearly map onto implementation on the ground. On the one hand, even in countries with very restrictive abortion laws, (clandestine) abortion rates are comparatively high, and legislation that criminalizes abortion is rarely enforced (Blofield 2006; Htun 2003). On the other hand, in countries that allow abortion under all or some circumstances, access to abortion is not guaranteed. In Argentina, for instance, different reports have stressed the difficulty in accessing abortion procedures both before and after legalization was enacted in early 2021.2

Sweeping changes in abortion politics are underway in the Americas. Argentina, Mexico, Colombia, and Uruguay have legalized abortion in recent years, marking a sea change in the most Catholic region of the world. At the same time, several states in the United States have restricted abortion access following the US Supreme Court’s decision to overturn Roe vs. Wade, and numerous Central American countries have moved to fully criminalize the practice. Abortion is now legal in countries where it was long taboo, whereas the United States is characterized by a patchwork of laws that spans from some of the most progressive in the world to near-total bans. What explains this changing panorama in terms of reproductive rights in the Americas?

In 2023, both Democratic and Republican elected officials supported banning official use of the gender-neutral term “Latinx.” Using a nationally representative survey sample, this study examines whether opposition to the gender-neutral term “Latinx” suggests a potential wedge issue that cuts across partisanship. We find that opposition to “Latinx” is significantly higher among Republican partisans, those who disapprove of Joe Biden as president, and those with “colder” feelings toward Democrats. Opposition to “Latinx” generally converges with factors that predict existing partisan divisions; where it diverges, it does not affect respondent evaluations of Biden or feelings about Democrats. Based on these findings, we conclude that gender-neutral language currently shows little potential as a wedge issue.

How can political scientists rigorously evaluate the predictive power of theories? Many peer-reviewed political science articles include predictions about future outcomes, and scholars make predictions on social media and other public forums. The prevalence of predictions suggests that scholars recognize the utility of leveraging theories for this purpose; however, the predictions often are not made in a manner that allows for rigorously evaluating their accuracy. Building on the increasing popularity of study preregistration in the social sciences, this article proposes “prediction registration” as a means for scholars to publish falsifiable, systematic, and verifiable theory-based predictions. Increasing the rigor of predictive theory testing can advance often-circular debates about accuracy and presents a “win-win” for scholars who aim to test the predictive power of theories. With a more rigorous approach, correct predictions would better demonstrate a theory’s ability to forecast outcomes, and missed predictions would reveal information that can be used to calibrate the theory.