Although much research confirms a gender gap in political science and its subfields internationally, only recently have scholars analyzed country-specific conditions for women within the field. Our study contributes to this national-level examination of gender diversity and inclusion by examining the extent to which a gender gap within the subfield of security studies, identified in the international literature, also is present in Canada. Research on gender representation and gendered experiences mostly centers on the academic workforce in the United States. However, in this article, we share the results of a multi-method investigation into the state of gender diversity in Canadian security studies—a national context in which the university sector has signaled a strong commitment to diversity and the government has actively promoted gender equality in official policy. By analyzing data collected from an online survey of security studies scholars in Canada and a document analysis of Canadian security-related journals and selected security studies syllabi, this contribution provides evidence that women are underrepresented in Canadian security studies and experience the subfield in less positive ways. We discuss the implications of these findings for the security studies subfield and suggest paths for future research and key recommendations.

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.

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.

This Special Issue presents a wide array of election forecasting models for the 2024 US elections. Most of these models generate forecasts for the presidential, congressional, and gubernatorial races. The contributions are characterized by the variety of their approaches: citizen forecasting, electronic markets, large language models, machine learning, poll-based models, and regression analysis. This introduction first summarizes some of the lessons and challenges of election forecasting. We then provide a brief context of the 2024 campaign and a short overview of the articles included in the Special Issue. The forecasts point to a tight presidential race. The two-party popular-vote predictions are almost evenly split, with some favoring Donald Trump and others Kamala Harris. However, among the models that offer an Electoral College forecast, three predict that Harris will win and five predict that Trump will return to the presidency.

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.

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.

This model generates projections of the national popular vote and Electoral College votes a year in advance of the U.S. Presidential Election, before each party’s nominees are known. It forecasts the Democratic two-party popular vote in each state and the District of Columbia. It uses four independent variables: national head-to-head polling data 13 months prior to the election, the states’ prior election result, a party-adjusted home state advantage dummy variable, and a party adjusted variable simply counting the number of consecutive terms the current incumbent party has occupied the White House. New to this year’s model is a polling average approach that encompasses all possible candidate matchups for whom data is available. This year’s forecast suggests a distinct possibility of an Electoral College misfire benefitting the Republicans.

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.

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.

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.

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.

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?

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.

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.

As the US Supreme Court was preparing to overturn Roe v. Wade, the Mexican Supreme Court issued a series of sweeping rulings to liberalize abortion—part of a larger trend across Latin America (Daby and Moseley 2022; Fernandez Anderson 2017; Reuterswärd 2020; Ruibal 2014). Mexico has created a nationwide standard of access to abortion services, whereas the United States has abandoned universal legal abortion and embraced a patchwork system in which each state has different laws regulating reproductive healthcare. Why are these two neighbors on such divergent paths? This contribution to the symposium compares the ways that federalism and judicial politics have interacted in Mexico and the United States to explain the different trajectories of abortion policy. The divergent paths of the United States and Mexico can be explained by the two countries’ different experiences with democracy and political and institutional differences between the judiciaries. A different civil-society and constitutional context also has played a role.

Despite governors’ crucial roles in shaping important policies, including abortion, education, and infrastructure, forecasters have paid little attention to gubernatorial elections. We posit that institutional idiosyncrasies and lack of public opinion data have exacerbated the classic problem facing all election forecasts: there are too many predictors and too few cases, leading to overfitting. To address these problems, we combine new governor and state-level presidential approval data with a machine-learning approach, LASSO, for variable selection. LASSO examines numerous variables but retains only those that substantively improve model performance. Results demonstrate the efficacy of gubernatorial and presidential approval ratings measured two quarters preelection in predicting both incumbent-party vote share and election winners in out-of-sample predictions. For 2022, our approach outperformed the Cook Political Report’s Partisan Voting Index and compared well with 538’s Election Day prediction. For 2024, our LASSO-Popularity model predictions indicate that it will likely be a difficult year for Democrats in gubernatorial contests.

The outcome of the 2016 election made it abundantly clear that victory in US presidential contests depends on the Electoral College much more than on direct universal suffrage. This fact points to the importance of using state-level models to arrive at adequate predictions of winners and losers in US presidential elections. In fact, the use of a model disaggregated to the state level and focusing on three types of measures—namely, changes in the unemployment rate, presidential popularity, and indicators of long-term patterns in the regional strength of the Democratic and Republican parties—has in the past enabled us to produce fairly accurate forecasts of the number of Electoral College votes for the presidential candidates of the two major American parties. In this article, we bring various modifications to this model to improve its overall accuracy. With Joe Biden out of the race, this revised model predicts that Donald Trump will succeed in winning back the presidency with 341 electoral votes against 197 for Kamala Harris.

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

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.

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.