Publications
Publications
Publications in English
Refereed Journal Articles
[1] Estimating the Partisan Bias of Japanese Legislative Redistricting Plans Using a Simulation Algorithm
Miyazaki, Sho, Kento Yamada, Kosuke Imai (2026+). Political Science Resaerch and Methods (conditional acceptance upon replication).
Abstract
Although partisan gerrymandering has been extensively studied in the United States, there exists little empirical research on legislative redistricting in other countries. We investigate the partisan bias of Japanese redistricting, in which a nonpartisan commission—appointed by the Prime Minister and approved by the Diet—draws districting plans. The existence of partisan bias in this setting remains a subject of debate in the literature. We estimate the partisan bias of the 2022 Japanese Lower House redistricting plans with a state-of-the-art redistricting simulation algorithm. By comparing the enacted plan with simulated nonpartisan baseline, we quantify the extent to which the enacted plan favors the ruling coalition. Our analysis shows that the Japanese redistricting process yields little partisan bias at both the prefecture and district levels.Publications in Japanese
[2] AI Political Advisor Pretending to be “Neutral”: Blind Spots in the Model’s Information Sources
(in Japanese, ‘Churitsu’ yosou AI advisor: Model no johogen ni shikaku ari).
Hall, Andrew B. and Sho Miyazaki (2026). Nikkei.
Abstract
We are invited to contribute to Nikkei, a Japanese national newspaper. This article is based on our subsctack article “AI Is A Shitty Political Advisor” and its Japanese version.[1] The Algorithms can resolve Japanese Electoral Malapportionment
(in Japanese, ‘Ippyo-no-kakusa’ wa saisentan no algorithm de kaizen dekiru).
Imai, Kosuke, Kento Yamada, Rei Yatsuhashi, and Sho Miyazaki (2022). Nikkei Business.