Publications

Kuriwaki, Shiro, Mason Reece, Samuel Baltz, Aleksandra Conevska, Joseph R. Loffredo, Can E. Mutlu, Taran Samarth, Kevin E. Acevedo Jetter, Zachary Djanogly Garai, Kate Murray, Shigeo Hirano, Jeffrey B. Lewis, James M. Snyder, Jr., and Charles Stewart, III. “Cast vote records: A database of ballots from the 2020 U.S. Election.” Scientific Data 11 (1304). DOI: 10.1038/s41597-024-04017-1. Public dataset is available here. Paper preprint is available here.

Abstract: Ballots are the core records of elections. Electronic records of actual ballots cast (cast vote records) are available to the public in some jurisdictions. However, they have been released in a variety of formats and have not been independently evaluated. Here we introduce a database of cast vote records from the 2020 U.S. general election. We downloaded publicly available unstandardized cast vote records, standardized them into a multi-state database, and extensively compared their totals to certified election results. Our release includes vote records for President, Governor, U.S. Senate and House, and state upper and lower chambers, covering 42.7 million voters in 20 states who voted for more than 2,200 candidates. This database serves as a uniquely granular administrative dataset for studying voting behavior and election administration. Using this data, we show that in battleground states, 1.9 percent of solid Republicans (as defined by their congressional and state legislative voting) in our database split their ticket for Joe Biden, while 1.2 percent of solid Democrats split their ticket for Donald Trump.

Jaffe, Jacob, Joseph R. Loffredo, Samuel Baltz, Alejandro Flores, and Charles Stewart III. 2024. “Trust in the Count: Improving Voter Confidence with Post-Election Audits.’’ Public Opinion Quarterly 88 (SI): 585-607. DOI: 10.1093/poq/nfae029. Replication materials are available here.

Abstract: Post-election audits are thought to bolster voter confidence in elections, but it is unclear which aspects of audits drive public trust. Using pre-registered vignette and conjoint survey experiments administered by YouGov on a sample of 2,000 American respondents, we find that how an audit is conducted is more important than what an audit finds. Structural features of audits, 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 discrepancy found. Moreover, while Democrats and Republicans have increasingly divided views of the state of democracy in the United States, they are similarly receptive to information presented about audits, and largely agree that audits are effective tools for detecting errors in vote counting. Our findings thus reinforce the expectation that audits do increase voter trust and suggest that election administrators can strengthen voter confidence by making audits as transparent as possible.

Under Review

Loffredo, Joseph R. and Suyeol Yun. 2025. “Agent-Enhanced Large Language Models for Researching Political Institutions.”

Abstract: The applications of Large Language Models (LLMs) in political science are rapidly expanding. This paper demonstrates how LLMs, when augmented with predefined functions and specialized tools, can serve as dynamic agents capable of streamlining tasks such as data collection, preprocessing, and analysis. Central to this approach is Agentic RAG, which equips LLMs with action-calling capabilities for interaction with external knowledge bases. Beyond information retrieval, LLM agents incorporate modular tools for tasks like document summarization, transcript coding, qualitative variable classification, and statistical modeling, enabling adaptability across diverse research contexts. To demonstrate the potential of this approach, we introduce CongressRA, an LLM agent designed to support scholars studying the U.S. Congress. Through this example, we highlight how LLM agents can reduce the costs of replicating, testing, and extending empirical research using the domain-specific data that drives the study of political institutions.

Working Papers

“Hidden Partisanship in American Elections” (with Mason Reece, Alejandro Flores, Samuel Baltz, and Charles Stewart III)

“Where We Vote: The Changing Landscape of Where Americans Cast Votes’’ (with Alejandro Flores)

“Motivating Participation: Encouraging Minority Voters to Overcome the Costs of Voting” (with Christine M. Slaughter)

“State Confidence in Elections: Results, Practice, and Policy” (with Charles Stewart III)

“Protecting their own: The use of local districting to create incumbency (dis)advantages” (with Michael Hankinson and Asya Magazinnik)