Publications

The administration of elections depends crucially upon the quality and integrity of voter registration databases. In addition, political scientists are increasingly using these databases in their research. However, these databases are dynamic, and may be subject to external manipulation and unintentional errors. In this paper, using data from Orange County, California, we develop two methods for evaluating the quality of voter registration data as it changes over time: (1) generating audit data by repeated record linkage across periodic snapshots of a given database, and monitoring it for sudden anomalous changes; and (2) identifying duplicates via an efficient, automated duplicate detection, and tracking new duplicates and deduplication efforts over time. We show that the generated data can serve not only to evaluate voter file quality and election integrity, but also as a novel source of data on election administration practices.

In recent years, a number of states have passed some version of automated voter registration (AVR). Implementation varies, but the core idea is to more aggressively promote voter registration as an option at the Department of Motor Vehicles. Evaluation of the impact of AVR has been limited thus far, mostly because AVR implementation has itself been limited. But post-reform data are now available for a number of states, and others that are considering adopting the reform are wondering what the effects of the laws have been in these states. What would registration and turnout have looked like in AVR states had the reform not been implemented? In this paper we take advantage of the first election cycle with significant post-AVR data across a range of states to explore the registration effects of AVR. We employ both difference-in-differences and synthetic control approaches to identify causality. Registration effects so far appear to have been solid overall and larger for Latinos. Evidence for Asian Americans and young people is more ambiguous, as is evidence for effects in individual states. We conclude with thoughts on future directions to help develop better estimates in these areas.

In voting, maps are traditionally used to indicate voter turnout and/or election results with respect to political parties. This paper explores the use of geospatial choropleth maps to analyze voter arrival patterns through a case study of using logs from electronic poll books (EPB) across the State of Rhode Island and Providence Plantations (RI). The EPB transaction logs record various metrics, such as the precinct number, location, and timestamp for every voter that checks in on Election Day. Geographically referenced jurisdiction datasets were plotted in ArcGIS and combined with the EPB transaction log data for the entire state’s 2018 Midterm elections to create the choropleth maps. The choropleth maps were shaded based on the percentage of total check-ins observed during selected time windows throughout the day.  

Analyses were undertaken to assess the visual representation of arrival densities for both the state and its major metropolitan area. Arrival observations statewide were highlighted and expanded in conjunction with known jurisdiction profiles. At the town/city level arrival patterns were identified based urban/suburban and rural areas. A precinct level analysis was performed in the metropolitan area and revealed differing arrival patterns within the City of Providence. General observations are provided based on visual inspection.  Identifying specific precinct groups with similar overarching trends of community voting behavior will require computationally based clustering methods. Future considerations of how data visualization of arrival patterns via EPBs are discussed. 

In 2005, the Texas Legislature allowed counties to move from precinct level voting to county-wide “vote centers” – locations in a county where all voters will vote, regardless of their address.  Vote centers are theoretically less expensive to administer and conveneit for many voters, but less is known about the impacts on specific communities.  Using Texas’ registered voters’ list from the Secretary of State’s Voting Division the project will use Geographic Information Systems (GIS) to calculate estimated driving distances and times from each registered voter’s residence to the voter’s vote center location. The restuls show that the displacement of traditional precinct level voting and the increase in distance between polling locations takes a greater toll on voter turnout for voters in rural counties and Latinos. 

 Street-level bureaucrats operate under fairly limited oversight, and are also the actors that de facto set the terms for policy implementation. This leaves room for discrepancies between the theoretical intent of a law and how it is actually applied by its most direct arbiters. In American elections, poll workers serve in this street-level bureaucrat position, bridging the gap between legal voting requirements required by state governments and citizen experiences at the polls. Using an examination of voter eligibility requirements and in-depth interviews conducted with poll workers in the city of Chicago—a jurisdiction where poll workers are asked to verify voter identity by signature—this paper examines what constitutes poll worker decisions about voter eligibility. Respondents offered detailed—and varied—information about what they look for when comparing signatures. Reflecting ambiguity in state election code, they also had different ideas about how to navigate mismatching signatures—ranging from relatively lenient responses to strict enforcement. Notably, they suggested that working in the same precinct and with the same people from election to election made the processing of voters easier. 

Post-election audits are thought to bolster voters’ confidence in elections, but it is unclear which aspects of audits drive public trust in election results and why. In a set of survey experiments fielded by YouGov to a sample of 2,000 Americans, we used both factorial and conjoint designs to understand which attributes of election audits are most important for increasing voter confidence in legitimate election results. Overall, we find that what an audit finds is much less important than how the audit is conducted, so long as the audit does not uncover exceptionally large errors. Structural features of the audit, like who conducts it and how its results are announced, turn out to be more consequential to voter evaluations of election results than the actual number of discrepancies found. Although voters are quick to pick up partisan cues about audits, this has not produced a broader polarization around election audits, and voters rationally do not punish an election in which the winner was called correctly for a few mis-counted votes. Our findings suggest that election administrators can bolster voter confidence through the design of election audits, without serious fear that turning up small numbers of errors will harm voter confidence.

The number of vote-by-mail (VBM) ballots in the 2020 presidential election reached record highs. Reasons for the sudden increase in voters using VBM ballots range from accessibility to social distancing restrictions and other COVID-19 pandemic health and safety concerns. In conjunction with other circumstances encircling the presidential election, the reporting of VBM results was delayed, which led to mistrust and contributed to mis- , dis-, and malinformation surrounding the election results. Ultimately, it was difficult for election officials to predict how long it would take to verify and tabulate VBM ballots, especially due to the rapid adoption and expansion of VBM. To understand the VBM verification and tabulation system, this research utilizes time studies to define rates, distributions, and processing times for VBM processes in order to support election officials in preparing for VBM results reporting in future elections. The data explored in this study were collected from several counties in the greater Salt Lake City region during the 2022 midterm election. These data consisted of time studies on manual and machine-supported VBM process steps, including, but not limited to, ballot arrival, signature verification, ballot extraction, tabulation, and adjudication. Through statistical methods, processing times, processing rates, and representative probability distributions for each VBM process step are defined. These data can assist in predicting the necessary workforce and forecasting the time to report
election results with existing equipment. The results aid in supporting election officials and administrators in making data-enabled decisions for future election planning and scheduling.

Does experience with voting by mail reduce mail-in voter fraud beliefs? Can personal experience counter partisan forces when the two conflict? I answer these questions by examining mail-in voter fraud beliefs in a single-state study following the 2020 presidential election, in which mail-in voter fraud became a more intense political and partisan issue. I focus on the ways in which partisan affiliation and personal experience may shape voters’ attitudes about mail-in voter fraud. Building on Zaller’s (1992) RAS model and Cramer and Toff’s (2017) framework of personal experience, I develop a theory to explain how firsthand experience can mitigate partisanship. Using OLS regression and instrumental variable analyses to test this theory, I find suggestive, causal evidence that voting by mail decreases beliefs about the prevalence of voter fraud. My results also confirm that affiliation with the Republican Party increases voter fraud beliefs. Including an interaction effect in the analysis provides no support for my hypothesis that the effect of voting by mail is conditioned on partisanship. I conclude from these findings that voting by mail can indeed mitigate the effect of partisanship on beliefs about fraud, despite the strength of partisan ties and polarization of the current political era. I consider the potential policy implications of these findings and argue that efforts to combat misinformation about mail-in voter fraud should consider interventions that increase voters’ experience with voting by mail.

In 2020, Alaska voters approved a ballot measure that implemented Ranked Choice Voting (RCV) in statewide and state legislative contests, as well as Congressional races. The 2022 election was the first cycle in which voters and election officials experienced voting using RCV rules. This paper examines the information landscape surrounding the RCV elections, including how organizations, candidates, political parties, and election officials communicate with voters in 2022 about the new rules. We use data gathered from tweets and newspaper coverage surrounding the election, as well as through interviews with Alaskan stakeholders. The paper also examines election results of primary and general elections from 2014 through 2022 to examine whether RCV created increased voter confusion. Finally, we note that Alaska provides unique opportunities to analyze RCV understanding among language minority communities (Tagalog, Spanish, and Native Alaskan). Therefore, we will also analyze if voters’ understanding of RCV rules varies by language communities, in addition to other demographic factors among voters.