Resources

In this PhD dissertation, Schmidt introduces optimization and simulation models to support the design and operation of resilient in-person election voting systems. Three core contributions: (1) a discrete-event simulation of pandemic-resilient polling-place design, with a case study of Milwaukee, WI; (2) the Polling Location Consolidation Problem (PLCP), an integer programming model applied to Richland County, SC; and (3) an optimization model for ballot drop box siting in Milwaukee.

This paper examines whether minority and Democratic-leaning voters in Florida receive lower poll worker staffing. Using data from multiple elections, authors find evidence of partisan disparities in staffing levels, with Democratic-trending counties receiving worse service relative to Republican-trending counties. They apply operations management methods to document systemic resource allocation inequities in polling place operations.

This paper shows how reporting data at the ballot-card level can reduce risk limiting audits sample sizes and improve audit efficiency.

In this paper, authors examine the effects of automatic voter registration (AVR) on both registration and turnout. They find that ind it does raise registration rates substantially, that the effect of AVR gradually builds the longer it is in place, and that the different types of AVR have significantly different effects on both registration and turnout.

In this article, authors argue that supported decision making is ideal for people with dynamic cognitive and functional impairments that place them at the margins of autonomy. This research supports the idea that people with cognitive
disabilities can make important decisions such as voting while relying on trusted assistors in executing those decisions.

This academic article studies how messages from political elites influence public confidence in elections and acceptance of democratic norms.

This research finds that a majority of Trump voters in the survey sample falsely believed that election fraud was widespread, and that Trump won the election. It also finds that Trump conceding or losing his legal challenges would likely lead a majority of Trump voters to accept Biden’s victory as legitimate, although 40% said they would continue to view Biden as illegitimate regardless.

Employing national surveys from 2012, 2016, 2018, and 2020, this paper that beliefs in election fraud are common and stable across time, and only occasionally relate to partisanship.

This research analyzes registrants in Wisconsin who were identified as potential movers and did not respond to a subsequent postcard. At least 4% of these registrants cast a ballot at their address of registration, with minority registrants twice as likely as white registrants to do so.

This book examines the dynamics behind shifts in voter registration rates across the states.

In this paper, authors match a high-quality, random sample of the U.S. population to multiple lists revealing that at least 11% of the adult citizenry is not on a voter list. An additional 12% is mislisted (i.e., not living at their recorded address).

In this paper, authors use snapshots of voter registration files (VRF) over time and machine learning models to test the effectiveness of unsupervised anomaly detection methods in detecting VRF modifications. They find that statistical models comparing administrative districts within a short time span and non-negative matrix factorization are most effective for surfacing anomalous events for review.