UCLA

In close elections, the losing side has an incentive to obtain evidence that the election result is incorrect. Sometimes this evidence comes in the form of court testimony from a sample of invalid voters, and this testimony is used to adjust vote totals (Borders v King County, 2005; Belcher v Mayor of Ann Arbor, 1978). However, while courts may be reluctant to make explicit findings about out-of-sample data (e.g. invalid voters that do not testify), when samples are used to adjust vote totals, the court is implicitly making findings about this out-of-sample data. In this paper, we show that the practice of adjusting vote totals on the basis of potentially unrepresentative samples can lead to incorrectly voided election results. More generally, we show that given the difficulties of sampling and non-response in this context, even when frame error is minimal and if voter testimony is accurate, such testimony has limited power to detect incorrect election results without precinct level polarization or the acceptance of large Type I error rates. Therefore in U.S. election disputes, even high quality post-vote vote-choice data will often not be sufficient to resolve contested elections without modeling assumptions (whether or not these assumptions are acknowledged).