More style, less work: card-style data decrease risk-limiting audit sample sizes
Amanda K. Glazer, Jacob V. Spertus, Philip B. Stark

TL;DR
This paper demonstrates that using card-style data (CSD) to identify which ballots contain specific contests significantly reduces the sample sizes needed for risk-limiting audits, especially in complex elections with multiple contests.
Contribution
It introduces the use of card-style data (CSD) to dramatically decrease RLA sample sizes by targeting ballots containing relevant contests, improving audit efficiency.
Findings
CSD reduces expected draws by 75% for single contests on 4-card ballots.
CSD reduces expected draws by over 95% for multiple contests with shared margins.
Savings in sample sizes can be several orders of magnitude in realistic election scenarios.
Abstract
U.S. elections rely heavily on computers such as voter registration databases, electronic pollbooks, voting machines, scanners, tabulators, and results reporting websites. These introduce digital threats to election outcomes. Risk-limiting audits (RLAs) mitigate threats to some of these systems by manually inspecting random samples of ballot cards. RLAs have a large chance of correcting wrong outcomes (by conducting a full manual tabulation of a trustworthy record of the votes), but can save labor when reported outcomes are correct. This efficiency is eroded when sampling cannot be targeted to ballot cards that contain the contest(s) under audit. If the sample is drawn from all cast cards, RLA sample sizes scale like the reciprocal of the fraction of ballot cards that contain the contest(s) under audit. That fraction shrinks as the number of cards per ballot grows (i.e., when elections…
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