Yuki Atsusaka

Welcome! I am an incoming Assistant Professor at the Hobby School of Public Affairs (University of Houston) and I hold a PhD in Political Science and MA in Statistics from Rice University. I also hold an MA in American Studies (with a focus on African American History and Culture) from Doshisha University.

In 2022-2023, I was a Guarini Dean’s Fellow in the Politics of Race and Ethnicity at Dartmouth College. My research focuses on electoral systems, race and ethnic politics, and political methodology. More specifically, I develop and apply new quantitative methods to study the effects of electoral engineering on minority representation in ethnically diverse democracies. My dissertation titled Political Methodologies for Electoral Engineering and Minority Representation received the John W. Gardner Award for the Best Dissertation in Social Sciences.

Substantive focus: electoral systems, minority representation
Methodological focus: ranking data, logical models

Email: yatsusak@central.uh.edu
Google Scholar: YukiAtsusaka
Dataverse: YukiAtsusaka
Twitter: @Yuki_Atsusaka
Curriculum Vitae: pdf
GitHub: here


News

April 21th, 2023
I presented my paper “When Does Ranked-Choice Voting Reduce Ideological and Ethnic Polarization” at Formal Theory Workshop at Washington University in St. Louis. Many thanks to Justin Fox! [Slides]
February 16th, 2023
I hosted a workshop titled “Diversity, Equity, and Inclusion and Political Science: A Roundtable” at Dartmouth College. Thanks all for coming! [Slides] [More info, registration]
February 1st & 3rd, 2023
On 2/1, I presented my talk “Quantitatively Predictive Logical Models” in the political methodology workshop. Many thanks to Silvia Kim and Jeff Gill. [Slides] On 2/3, I talked about my paper “Causal Inference with Ranking Data” in the department talk series. Big thanks to Andy Ballard and Laura Paler! Both at American University. [Slides]


Publications

2. Yuki Atsusaka and Randolph T. Stevenson. 2023. A Bias-Corrected Estimator for the Crosswise Model with Inattentive Respondents Political Analysis 31 (1) 134-148. [R Package: cWise] [Article Summary] [Replication Files] [Preprint]

1. Yuki Atsusaka. 2021. A Logical Model for Predicting Minority Representation: Application to Redistricting and Voting Rights Cases American Political Science Review 115 (4), 1210-1225. [R Package: logical] [Article Summary] [Replication Files]

Working Papers

2. Yuki Atsusaka. “Causal Inference with Ranking Data: Application to Blame Attribution in Police Violence and Ballot Order Effects in Ranked-Choice Voting

1.Yuki Atsusaka and Theodore Landsman. “Does Ranked-Choice Voting Reduce Racial Polarization? Evidence from Agent-Based Modeling and Bay Area Mayoral Elections
(A winner of New America’s Electoral Reform Research Group Grant)


Work in Progress

“Addressing Measurement Errors in Ranking Questions for Social Sciences” (with Seo-young Silvia Kim)
“Making Predictions Without a Black Box: A Logical Model for Inter and Intra-Party Competition in Open-List Proportional Representation” (with Francisco Cantu)


Software

  1. cWise: A (Cross)Wise Method to Analyze Sensitive Survey Questions
  2. logical: Computing and Visualizing Quantitative Predictions of Logical Models

Teaching

As an instructor, I have taught the Math Prep (aka Math Prefresher) for the first-year graduate students in 2018-2019, Social Analysis and Simulation in R for the second-year graduate students in 2019, and Ecological Inference in Advanced Political Methodology in 2019. In addition, I have worked as a teaching assistant for graduate courses such as Causal Inference (Fall 2019), Advanced Maximum Likelihood Estimation (Spring 2019), and Machine Learning/Computational Social Science (Fall 2020) and undergraduate classes such as Applied Research Methods (2021-2022). I have also founded and organized the Rice Methodology Research Group in the Department of Political Science.