Resources

The Center for Civic Design provides this toolkit for election officials to create educational materials about Election Day and post-election processes, adaptable to any jurisdiction. It helps election offices communicate clearly with voters and poll workers about what happens on and after Election Day.

Registered voters in some legislative districts in Los Angeles County were subjected to universal voting by mail in the March 2020 primary. This research indicate that voter turnout increased by 3 to 4 percentage points for voters who do not automatically receive a mail ballot, and the increase is generally larger for registered partisan voters than those without a party affiliation.

This tool provides a training guide and customizable slide presentation to help election officials prepare poll workers to assist voters with disabilities in marking, verifying, and casting their ballots while preserving voter independence and privacy. It was published as NIST VTS 100-2.

The Accessible Voting Machines Calculator is a simulation tool that helps election officials estimate how many accessible voting machines are needed to maintain reasonable voter wait times. Officials can enter information about thier voting process and voter population and run simulations to produce recommended resource allocations.

In this paper, authors use a national survey of poll workers from the 2022 midterm election to analyze whether there are systematic differences between experienced and inexperienced poll workers in how they manage polling sites. They finds that experienced poll workers are more likely to say that their training prepared them for the election, yet their experience also correlates with more conflicts involving poll watchers and voters. This research fills a crucial gap in understanding how poll workers' experience influences Election Day operations.

This resource consists of a collection of EAC best practices, materials, and guidance to support election officials in delivering equal and accessible voting experiences, including resources on ADA-compliant equipment, accessible polling place design, and serving voters with disabilities.

This resources features a guidance handbook for testing voting systems against the usability and accessibility requirements in the Voluntary Voting System Guidelines (VVSG) 2.0. It supports election officials and testing labs in evaluating whether voting equipment meets federal usability standards.

In this paper, authors draw upon the 2016 and 2020 Cooperative Election Study to analyze the likelihood that Trump supporters: (1) voted by mail, (2) self-reported voting by mail, and (3) self-reported not voting by mail when they did (misreporting VBM). In 2020, Trump supporters were markedly less likely to cast a VBM ballot and were also significantly more likely to disclaim voting by mail when they actually did.

The Hand Count Workload Calculator is a simulation tool that helps election officials estimate the resources needed to conduct a hand count of ballots, whether for initial tabulation, an audit, or a recount. Officials can determine how many counting teams are needed to meet a deadline or how long a count will take with a fixed staff. Default timing data is based on observational data from a Northeastern state in November 2024.

The survey included an expansive set of disability questions and validated voter turnout responses against state voter files. The analyses reveal a high disability incidence; large disability turnout gaps; and even greater gaps estimated with validated compared to reported turnout. Much smaller turnout gaps and better voting experiences are found in the states that conduct their elections with all-mail voting.

This structured testing protocol can help identify e-pollbook usability problems before Election Day, using mock-election scenarios with poll workers. Helps election officials evaluate existing systems and make informed procurement decisions.

This research's findings suggest that signature validation, which serves as a primary safeguard for mail voting integrity, may be systematically influenced by underlying biases