This article investigates whether campaign contributions and lobbying are complementary, substitutive, or distinct forms of organizational political engagement. Our study reveals minimal overlap between organizations that engage in lobbying and those that make campaign contributions despite the perception that these activities are interchangeable forms of “money in politics.” Using comprehensive contribution and lobbying report data from 1998 to 2018, we find that most politically active organizations focus exclusively on either lobbying or making campaign contributions. Only a small percentage of organizations engage in both activities. This finding challenges the assumption that these forms of political activity are inherently linked. The majority of organizations engaged in political activity do so exclusively through lobbying. However, the top lobbying groups spend the most money and almost always have affiliated political action committees (PACs). Most lobbying money is spent by a small number of big spenders—organizations that also have affiliated PACs. Organizations that both lobby and make campaign contributions tend to be well resourced and rare.

There are few clear-cut examples of countries that have abolished or introduced compulsory voting. When the Netherlands abolished the system in 1971, Irwin (1974) documented how this led to a sharp reduction in voter turnout, especially among young people, women, and those with little political interest. Flanders, the largest autonomous region of Belgium, abolished compulsory voting in October 2024, and we accessed panel data collected before and after the event. We replicate Irwin’s analysis because electoral participation in the region decreased by almost 26 percentage points. Remarkably, our results are similar regarding the effect of gender and political interest, but we do not find a significant effect of educational level. Therefore, the normative argument that abolishing compulsory voting leads to more inequality based on education is not supported by our results. We do not find substantial consequences for the average policy input.

During the 2020 presidential election, the Trump campaign incorrectly claimed that a lower-than-expected proportion of Republican votes among populations living on and near military bases signaled evidence of voter fraud. These claims rested on assumptions that military bases and their surrounding communities are strongholds for political conservativism––a belief held by scholars, pundits, and politicians alike. While the logic behind these arguments is appealing, it fails to consider the complexities surrounding military service and institutions, political geography, partisan preferences, and voting behavior. We directly test the notion that communities close to military bases will be and vote more Republican. Using three different but related empirical strategies that rely on a large dataset spanning 16 years, we find evidence contradicting the conventional wisdom. No consistent pattern across military installations exists. While some lean Republican, others lean Democratic, and the vast majority exhibit no party pattern at all. Our results carry implications for American civil–military relations and the maintenance of American democracy.

In the past five years, 13 counties in Eastern Oregon have voted in nonbinding referendums to separate from the liberal state of Oregon to join the conservative state of Idaho. Drawing on theories of secessionism and irredentism, this article examines the drivers of the so-called Greater Idaho movement by administering a survey in these separatist counties. Our findings indicate that economic discontent and a strong regional identity are more important than fears or partisanship in determining support for moving the interstate border. Our study suggests that more inclusive governance may help to overcome ideological polarization in this case and offers insights into how political divisions may be managed to prevent separatist violence in the United States more generally. We conclude that political minorities need to believe that they have a voice in the system so that they do not mobilize for exit.

This article explores the use of large language models (LLMs), specifically GPT, for enhancing information extraction from unstructured text in political science research. By automating the retrieval of explicit details from sources including historical documents, meeting minutes, news articles, and unstructured search results, GPT significantly reduces the time and resources required for data collection. The study highlights how GPT complements human research assistants, combining automated efficiency with human oversight to improve the reliability and depth of research. This integration not only makes comprehensive data collection more accessible; it also increases the overall research efficiency and scope of research. The article highlights GPT’s unique capabilities in information extraction and its potential to advance empirical research in the field. Additionally, we discuss ethical concerns related to student employment, privacy, bias, and environmental impact associated with the use of LLMs.

Social construction theory postulates that policy outcomes depend on whether target groups are imagined by the public as deserving or undeserving. However, recent evidence demonstrates that the constructions in question are contentious rather than uniformly shared. This article applies the conjoint-experimental method to measure the social construction of immigrant (il)legality and to assess its political implications. We demonstrate that it is multidimensional because the absence of legal status is associated with receipt of government benefits, Hispanic origin, police record, poor English fluency, and less education. We also show that whereas the receipt of government benefits is not associated with the absence of legal status among most respondents, individuals who hold this association support stricter immigration-enforcement policies. Our findings corroborate the social construction approach but also indicate that researchers may want to measure multiple dimensions of target-group constructions in addition to deservingness.

The “home–field” dichotomy has long been a core assumption of fieldwork in political science. As in other social science disciplines, political scientists rely on these categories to contextualize our research within particular time–space nexuses and to separate our personal lives and private dwellings and institutions from our sources, participants, and broader research environments. Although the spatial, temporal, and emotional divisions between our “homes” and “fields” have always been arbitrary, they are increasingly blurred when we use remote and online methods for research, especially for qualitative studies. This article problematizes the home–field dichotomy within the context of remote and online political science field research. We contend that the overlap of our homes and fields in digital fieldwork poses different challenges for our professional boundaries than offline research, particularly in terms of separating our personal and research lives, mitigating risk, and protecting our mental health. Given the growing use of remote and online methods, we argue that the discipline of political science must account more seriously for the muddling of our homes and fields to support rigorous, transparent, and ethical empirical research.

This article shows how the sudden introduction of large language models (LLMs) has allowed a sudden, significant increase in the ability of political science professionals to plagiarize their articles by prompting LLMs to write for them. Evidence of this is shown through a brief overview of the limitations of LLMs and by searching for words that are disproportionately used by the most popular LLM, ChatGPT, in peer-reviewed articles. What is found is a rapid spike in the use of words that are unremarkable except for their popularity in ChatGPT’s output as determined by an AI professional. This shows that this method can be used to indicate the likelihood of plagiarism in a given article. It then concludes with the limitations of this keyword detection method and recommendations for limiting LLM plagiarism in the field of political science as a whole.

The discipline of political science faces significant disparities in the representation and participation of underrepresented groups in graduate education, including first-generation college students, racial and ethnic minorities, and women. Underrepresentation has a wide variety of limiting effects, including a narrower range of questions being explored within the field. This article proposes a template for teaching and mentoring undergraduate students from underrepresented backgrounds to enhance their opportunities in graduate programs. Specifically, it examines the Mobilization and Political Economy (MPE) Summer Program, an in-residence graduate pipeline program designed to equip participants to study and conduct research on political mobilization, social movements, and political economy. The MPE Summer Program aims to develop and sustain broad-scale collaborative infrastructures that prefigure reciprocal and equitable pathways to increase participation in the social sciences across the United States.

Since the outbreak of the COVID-19 pandemic, scholars have debated whether digital fieldwork can effectively substitute for on-site field research. The prevailing view is that digital fieldwork is a last resort when in-person access is limited. Reflecting on my recent field research in Vietnam and Malaysia, I advocate for integrating digital and on-site fieldwork as complementary components of the research process. This approach is particularly valuable for scholars who are unable to spend extended periods in the field. The integrative approach helps researchers (a) prepare effectively for on-site fieldwork, (b) adapt the data collection process flexibly while in the field, and (c) continue data collection and maintain working relationships with local networks after leaving the field. Through this reflection, I encourage researchers to normalize the integration of both methodologies to leverage the strengths of each approach.

We collected data on every tenure-track (TT) faculty member in the 122 PhD-granting political science departments in the United States to identify which graduate programs place faculty members in our discipline’s research universities. The top 20% of departments produced 75% of all faculty and the bottom 50% accounted for less than 5% of all TT faculty members at a research university. Forty-nine programs did not have a single graduate placed in a TT position at a PhD-granting department in the past 10 years, and 18 programs did not have a single graduate in a TT position at a PhD-granting department at all. The overwhelming majority of TT faculty members are at a lower or equally ranked department. The results have important implications for prospective graduate students and the future of our discipline.

When we open a random political science journal, we have a roughly two-to-one chance that the article is written by a man. Beyond this general finding, we know little about the gender gaps within political science knowledge production: Are women more represented in lower- or higher-ranked journals? Do they publish more single-authored or multiauthored papers? Do they publish more content in some fields than in others? This article answers these questions by analyzing an original dataset based on the International Political Science Abstracts (a peer-reviewed academic journal) from 2022 consisting of more than 7,000 articles and more than 13,000 authors in political science from around the world. We find no difference in the percentage of female authors between higher- and lower-ranked journals. We find a slightly higher propensity among women to publish in teams. Regarding subfields of study, women are particularly underrepresented in political theory, in which they publish only 21.6% of all published articles—which is an approximate 12-percentage-point deviation from the overall average.

Classroom discussions of current events and controversial topics can devolve into unproductive and highly charged debates. This article describes an in-class exercise used to foster respect during difficult conversations by encouraging students to design rules for discussions and guidelines to create a safe space for dialogue. This activity relies on three underlying principles: trust, empowerment, and empathy. These principles can be integrated into a broader pedagogical approach that emphasizes a democratic classroom and active learning. Student feedback shows that the intervention can be useful for promoting respectful and engaging discussions during moments of tension and polarization. However, an emphasis on civility also may undermine the diversity of opinions and require respecting students’ silences.

Giving students choice in how they are assessed, known as assessment optionality, is an innovation in assessment that has gained attention in recent years for its potential for improving inclusivity and engagement in teaching and learning. However, although assessment innovations can be beneficial, the process of changing long-established norms can be difficult. Political science is a field in which the Scholarship of Teaching and Learning literature has long noted that there is limited pedagogical innovation. This resistance to innovation creates a challenge for those working in the field—stronger and specific arguments must be developed to justify changes to curricula. This article presents the results of participatory research with political science students to explore whether a subject-specific case can be made for the use of assessment optionality in the discipline. The study explores political science students’ understandings of costs and benefits of assessment optionality and shares co-created recommendations for the potential application of the practice.