About

Justin Ryan Grimmer is the Morris M. Doyle Centennial Professor in Public Policy in Stanford University's Department of Political Science. He is also a Senior Fellow at the Hoover Institution and serves as Co-Director of the Democracy and Polarization Lab. His research focuses on Congress, elections, social media, and data science, contributing to the understanding of American politics through these areas.

Research topics

• Computer Science
• Political Science
• Artificial Intelligence
• Machine Learning
• Law
• Psychology
• Data science
• Sociology
• Natural Language Processing
• Social Science
• Mathematics
• Public relations
• Advertising
• Media studies
• Criminology
• Mathematics education
• Business
• Econometrics
• Knowledge management
• Epistemology
• Social psychology
• Psychiatry

Selected publications

• How shifting priorities and capacity affect policy work and constituency service: Evidence from a census of legislator requests to U.S. federal agencies

  American Journal of Political Science · 2026-01-30

  articleOpen accessSenior author

  Abstract When elected officials gain power, do they use it to provide more constituent service or affect policy? The answer informs debates over how legislator capacity, term limits, and institutional positions affect legislator behavior. We distinguish two countervailing effects of increased institutional power: shifting priorities and increased capacity. To assess how institutional power shapes behavior, we assemble a massive new database of 611,239 legislator requests to a near census of federal departments, agencies, and subagencies between 2007 and 2020. We find that legislators prioritize policy work as they gain institutional power (e.g., become a committee chair) but simultaneously maintain their levels of constituency service. Moreover, when a new legislator replaces an experienced legislator, the district receives less constituency service and less policy work. Rather than long‐serving and powerful elected officials diverting attention from constituents, their increased capacity enables them to maintain levels of constituency service, even as they prioritize policy work.

  PublisherOA PDFDOI

• Are Close Elections Random?

  SSRN Electronic Journal · 2025-01-01 · 73 citations

  articleOpen access1st authorCorresponding
  PublisherDOI

• Assessing the Reliability of Probabilistic US Presidential Election Forecasts May Take Decades

  2024-08-26 · 4 citations

  preprintOpen access1st authorCorresponding

  Probabilistic election forecasts dominate public debate, drive obsessive media discussion, and influence campaign strategy. But in recent presidential elections, apparent predictive failures and growing evidence of harm have led to increasing criticism of forecasts and horse-race campaign coverage. Regardless of their underlying ability to predict the future, we show that society simply lacks sufficient data to evaluate forecasts empirically. Presidential elections are rare events, meaning there is little evidence to support claims of forecasting prowess. Moreover, we show that the seemingly large number of state-level results provide little additional leverage for assessment, because determining winners requires the weighted aggregation of individual state winners and because of substantial within-year correlation. We demonstrate that scientists and voters are decades to millennia away from assessing whether probabilistic forecasting provides reliable insights into election outcomes. Forecasters' claims of superior performance and scientific rigor should be tempered to match the limited available empirical evidence.

  PublisherOA PDFDOI

• A Statistical Framework to Engage the Problem of Disengaged Survey Respondents: Measuring Public Support for Partisan Violence

  SSRN Electronic Journal · 2024-01-01 · 2 citations

  preprintOpen access
  PublisherDOI

• AutoPersuade: A Framework for Evaluating and Explaining Persuasive Arguments

  2024-01-01 · 3 citations

  articleOpen access

  We introduce AutoPersuade, a three-part framework for constructing persuasive messages.First, we curate a large dataset of arguments with human evaluations.Next, we develop a novel topic model to identify argument features that influence persuasiveness.Finally, we use this model to predict the effectiveness of new arguments and assess the causal impact of different components to provide explanations.We validate AutoPersuade through an experimental study on arguments for veganism, demonstrating its effectiveness with human studies and out-of-sample predictions.

  PublisherOA PDFDOI

• How Election Rules Affect Who Wins

  The Journal of Legal Analysis · 2024-01-01 · 17 citations

  articleOpen access1st author

  Abstract Contemporary election reforms that are purported to increase or decrease turnout tend to have negligible effects on election outcomes. We offer an analytical framework to explain why. Contrary to heated political rhetoric, election policies have small effects on outcomes because they tend to target small shares of the electorate, have a small effect on turnout, and/or affect voters who are relatively balanced in their partisanship. After developing this framework, we address how the findings bear on minority voting rights. We then show that countermobilization from political parties cannot explain the small effects of election laws. We explain that even when a state passes multiple policies at the same time, the reforms will still only have a marginal effect on turnout and an ambiguous effect on who wins. Finally, we explain what policies should raise alarm about affecting outcomes.

  PublisherOA PDFDOI

• Evaluating a New Generation of Expansive Claims about Vote Manipulation

  Election Law Journal Rules Politics and Policy · 2024-04-01 · 3 citations

  article1st authorCorresponding

  In the wake of Donald Trump's attempt to overturn the 2020 presidential election, a cottage industry of conspiracy theorists has advanced ever more expansive claims of vote manipulation, going so far as to allege that all American elections are subject to manipulation—even in largely Republican states. In the extreme, these conspiracy theorists argue that candidates in U.S. elections are selected rather than elected. We evaluate two recent sets of claims about vote manipulation that allege algorithms are used to shift votes towards preferred candidates. Even though these claims are distinct, they fail for similar reasons. For example, both sets of claims assert that “unnaturally” accurate predictions of election results are evidence of vote manipulation, an allegation that is a result of predicting a variable with itself. Furthermore, both claims make easily refuted errors in logic and data analysis and in addition misrepresent historical election patterns. While recent claims about vote manipulation are prima facie outlandish, their effects on policy and the public are real. Refuting false claims about vote manipulation is essential to ensuring the continued functioning of U.S. elections and American democracy more generally.

  PublisherDOI

• Who Are the Election Skeptics? Evidence from the 2022 Midterm Elections

  Election Law Journal Rules Politics and Policy · 2024-09-20 · 3 citations

  article

  Faith in American elections is eroding, with politicians frequently questioning the legitimacy of election results and spreading misinformation about voter fraud. Substantial work has been done to refute misinformation and increase confidence in elections, but often without a clear picture of who skeptics are and why they are skeptical. Using a nationally representative survey from around the 2022 midterm election ( N = 5,244) and beyond ( N = 77,325), we provide a comprehensive profile of election skeptics: their prevalence, views, and justifications. Our use of quantitative and qualitative data reveals a more milquetoast portrait of skeptics. Skeptics are demographically closer to the broader electorate than not, and the self-reported underpinnings of skepticism are more mundane than conspiratorial. Over half of skeptics claim they are skeptical because of how elections are run and nearly one-in-five skeptics claim they are skeptical because of the other party’s performance in recent elections, which we corroborate through an event study of the 2022 election.

  PublisherDOI

• Measuring the Contribution of Voting Blocs to Election Outcomes

  The Journal of Politics · 2024-09-17 · 5 citations

  article1st authorCorresponding

  To interpret elections, social scientists and media pundits often ask: How much did particular groups, or voting blocs, contribute to a candidate’s vote total? The default tool for studying voter behavior—regressions of vote choice on voter characteristics—is useful for evaluating correlates and determinants of vote choice but is incapable of assessing how many votes a group contributes. Accounting for votes also requires knowing a group’s size and its turnout rate. We introduce a set of tools for estimating how many votes a bloc gives to a candidate, how voting bloc patterns differ from prior elections, and how support changes under counterfactuals. We apply these tools to study US presidential elections, demonstrating that there is little evidence to show Black and Latino voters are shifting toward Republicans in recent elections and that Donald Trump’s support was concentrated among voters with moderate attitudes toward racial outgroups.

  PublisherDOI

• AutoPersuade: A Framework for Evaluating and Explaining Persuasive Arguments

  arXiv (Cornell University) · 2024-10-11

  preprintOpen access

  We introduce AutoPersuade, a three-part framework for constructing persuasive messages. First, we curate a large dataset of arguments with human evaluations. Next, we develop a novel topic model to identify argument features that influence persuasiveness. Finally, we use this model to predict the effectiveness of new arguments and assess the causal impact of different components to provide explanations. We validate AutoPersuade through an experimental study on arguments for veganism, demonstrating its effectiveness with human studies and out-of-sample predictions.

  PublisherOA PDFDOI

Frequent coauthors

• Sean Westwood

  31 shared

• Solomon Messing

  18 shared

• Brandon Stewart

  17 shared

• Margaret E. Roberts

  12 shared

• Matthew Tyler

  Rice University

  10 shared

• Gary King

  Harvard University Press

  8 shared

• Cole Tanigawa-Lau

  7 shared

• Christian Fong

  University of Michigan–Ann Arbor

  7 shared

Labs

• Democracy and Polarization LabPI

Education

• Ph.D., Political Science

  Stanford University

  2009

• M.A., Political Science

  University of California, Berkeley

  2004

• B.A., Political Science

  University of California, Los Angeles

  2001