Research

Research Interests

Substantive: American political institutions, Congressional policymaking & oversight capacity, legislative support agencies, political behavior, ideology and public policy

Methods: causal inference and causal machine learning, Monte Carlo methods, predictive modeling, design-based inference, experiments, measurement, game theory, text analysis

Publications

Affect, Not Ideology: The Heterogeneous Effects of Political Cues on Policy Support
with Nicolás de la Cerda and Sam Fuller · Political Behavior, 2025 · WPSA 2023

Book Project

Advanced Machine Learning for Experiments in the Social Sciences
with Christopher D. Hare and Sam Fuller · Advance contract, Cambridge Elements: Experimental Political Science · Expected 2026-2027

Causal Forest and Doubly Robust Machine Learning for Political Science
with Sam Fuller · Companion paper · MPSA 2023 · APSA 2024

Research under Review

Hostile Principals and The Beginning of the End of the Legislative State
MPSA 2024 · previously titled “Did the Republican Revolution Hamstring Congressional Oversight? Evidence from 55,000 GAO Reports”

Are Random Forests Still “Good Enough”? Tabular Prior-Data Fitted Networks for Predictive and Causal Tasks

How Model Choice Obscures Forecast Uncertainty: The Rashomon Effect and the 2026 Senate
with Christopher D. Hare

Leaving Money on the Table: A Monte-Carlo Study Comparing Causal Forest and Standard Regression Models for Experiments
with Sam Fuller · APSA 2025

What Predicts Support for Political Violence? Results from a Machine Learning Meta-Reanalysis
with Sam Fuller and Alexa Federice · Harvard American Politics Research Workshop 2024 · MPSA 2025 · APSA 2025

The Changing Landscape of Democratic (Dis)Satisfaction: Results from the American National Election Study 1996–2024
with Sam Fuller and Neil S. Williams · MPSA 2026

Selected Research in Preparation

Populism and the Political Economy of Congressional Professionalization

ocx: Fast and Improved (Ordinal) Optimal Classification
with Christopher D. Hare, Tzu-Ping Liu, and Keith T. Poole

The Balance Permutation Test: A Machine Learning Replacement for Balance Tables
with Sam Fuller · UC Davis Political Science Research Workshop · ICPSR 2024

Rational Voting in the Age of Ideological Polarization & Responsible Parties: Examining Presidential Elections from 1972–2024
with Carlos Algara and Sam Fuller · SPSA 2026

The Dangers of Calculating Conditional Effects: A Reevaluation of Barber and Pope (2019)
with Sam Fuller · MPSA 2024