The greatest threat of democratic breakdown stems from the federal structure of the US Constitution and from false claims of election fraud with the potential for state- or congressional- level reversals of popular vote outcomes. The potential for such a breakdown was revealed by the events of January 6, 2021, with tens of millions of voters still believing in the big lie and the repetition of that lie by legislators and government officials. It is exacerbated by hyperpolarization, minoritarian control caused by partisan gerrymandering for state legislative districts and in the US House, malapportionment in the US Senate, and the highest likelihood of Electoral College reversals of popular vote outcomes in more than a century. Democratic breakdown is also made more likely by recent legislation that makes it easier for legislators in some gerrymandered states to reverse the outcomes of the popular vote in their states.

This article builds on work by Devine and Kopko (2021) and Lacy and Burden (1999) who estimated a probit model of candidate choice from nationally representative survey data to determine the second choice of third-party voters. Using this model on 2020 election data, we show that the Libertarian candidate Jo Jorgenson probably cost Donald Trump victory in at least two states: Arizona and Georgia. Additionally, the popular-vote margin enjoyed by Joe Biden could have been between 260,000 and 525,000 fewer votes, using conservative estimates. The motivation for this article is to provide contrary evidence for two main misconceptions. First, that third-party candidates are “spoiling” elections for the Democrats. Our evidence clearly shows that third parties have the potential to hurt either of the two main parties; however, in 2020, it was Donald Trump who was hurt the most, although not consequentially. Second, some reformers believe that ranked-choice voting benefits the Democrats; again, we show that—all else being equal—in the 2020 presidential election, it was the Republicans who would have benefited by the change in rules because the majority of third-party votes went to the Libertarian candidate, whose voters prefer Republicans over Democrats 60% to 32%.

This article uses data collected from Google Scholar to identify characteristics of scholars who have chosen to create a Google Scholar profile. Among tenured and tenure-track faculty with full-time appointments in PhD-granting political science departments, we find that only 43.7% have created a profile. However, among R1 faculty, young and early-career faculty are more likely to have Google Scholar profiles than those in older cohorts. Although subfield differences are largely nonexistent, there is a notably low proportion of theory faculty with profiles and a slightly higher proportion with profiles among methodologists. Moreover, within cohorts, those who are highly cited are more likely to have profiles than those who have low citation counts. We conclude by discussing implications of our findings, the increasing usage of Google Scholar and profiles, and the increasing importance of an online presence in the academy.

Though African-American and Latino electoral success in state legislative and congressional elections continues to occur almost entirely in majority-minority districts, minorities now have new opportunities in districts that are only 40–50% minority. This success can primarily be explained in terms of a curvilinear model that generates a “sweet spot” of maximum likelihood of minority candidate electoral success as a function of minority population share of the district and the proportion of the district that votes Republican. Past racial redistricting legal challenges often focused on cracking concentrated racial minorities to prevent the creation of majority-minority districts. Future lawsuits may also follow in the steps of recent successful court challenges against racially motivated packing that resulted in the reduction of minority population percentage in a previously majority-minority district in order to enhance minority opportunity in an adjacent non-majority-minority district.

Using updated data from 2002 and 2017 on the political science discipline, we show how the cohort and gender composition of US PhD-granting departments has changed dramatically over time. Integrating 2002 and 2017 data, we examine overall patterns and gender differences in job mobility, tenure and promotion, and university prestige level among non-emeritus 2002 faculty, controlling for cohort effects. Even with this control, we find strong gender effects in some of these success dimensions. We then introduce another variable, citation counts, and find that women are consistently less cited than men, with important variations in the pattern across different cohorts. A control for citation counts show that some of these gender differences tend to disappear and we consider possible explanations for these findings.

This article updates the Masuoka, Grofman, and Feld 2002 dataset that identified the then-3,719 faculty in political science PhD-granting departments in the United States. That dataset contained information about each faculty member, including date and PhD-granting department, lifetime citation counts, fields of interest, and school of employment. We similarly create a database with the 4,089 currently tenured or tenure-track faculty, along with emeritus faculty, at US PhD-granting departments ca. 2017–2018. Using Google Scholar Profiles, along with manual counts for those who do not have a profile, we sort the dataset by citation count, PhD cohort, field of interest, and gender. This article identifies the 100 currently most-cited scholars, the 25 most-cited in each PhD cohort and subfield, the 40 most-cited women scholars, and the 25 most-cited emeriti. The full list of The Political Science 400 is available in an online appendix.

The fact that two senators are elected from each state offers the potential for natural paired comparisons. In particular, examining historical and geographic patterns in terms of changes in the number of divided US Senate delegations (i.e., states whose two senators are of different parties) is a useful route to testing competing models of American politics, including theories of split-ticket voting, party polarization, and realignment. Brunell and Grofman (1998) used divided Senate delegations to indirectly examine evidence for realignment. We hypothesized that a partisan realignment will necessarily lead to a cyclical pattern in the number of divided Senate delegations. We predicted that the number of divided Senate delegations at the state level would decline after 1996 because we conjectured that there had been a realignment cusp around 1980. We tested this prediction with data from 1952–2016 and our prediction was confirmed.

The Shapley-Owen value (SOV, Owen and Shapley 1989, Optimal location of candidates in ideological space. International Journal of Game Theory 125–42), a generalization of the Shapley-Shubik value applicable to spatial voting games, is an important concept in that it takes us away from a priori concepts of power to notions of power that are directly tied to the ideological proximity of actors. SOVs can also be used to locate the spatial analogue to the Copeland winner, the strong point, the point with smallest win-set, which is a plausible solution concept for games without cores. However, for spatial voting games with many voters, until recently, it was too computationally difficult to calculate SOVs, and thus, it was impossible to find the strong point analytically. After reviewing the properties of the SOV, such as the result proven by Shapley and Owen that size of win sets increases with the square of distance as we move away from the strong point along any ray, we offer a computer algorithm for computing SOVs that can readily find such values even for legislatures the size of the U.S. House of Representatives or the Russian Duma. We use these values to identify the strong point and show its location with respect to the uncovered set, for several of the U.S. congresses analyzed in Bianco, Jeliazkov, and Sened (2004, The limits of legislative actions: Determining the set of enactable outcomes given legislators preferences. Political Analysis 12:256–76) and for several sessions of the Russian Duma. We then look at many of the experimental committee voting games previously analyzed by Bianco et al. (2006, A theory waiting to be discovered and used: A reanalysis of canonical experiments on majority-rule decision making. Journal of Politics 68:838–51) and show how outcomes in these games tend to be points with small win sets located near to the strong point. We also consider how SOVs can be applied to a lobbying game in a committee of the U.S. Senate.