Resolving Contested Elections: The Limited Power of Post-Vote Vote-Choice Data
解决选举争议：投票后投票选择数据的有限检验功效AI 解读 ↓
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AI 根据所提供的论文材料归类：摘要研究选举调查的样本代表性与检验功效，投票选择数据本身不足以归入离散选择模型。
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解决选举争议：投票后投票选择数据的有限检验功效
- 研究问题
- 在接近的选举中，依据部分无效选民的庭审证词调整票数会带来哪些错误判决风险，投票后调查又有多大能力识别错误结果？
- 方法与思路
- 作者分析非代表性样本、抽样与无回应如何影响票数调整及检验功效，并讨论选区极化和第一类错误容忍度的作用。
- 材料陈述的贡献
- 摘要称，非代表性证词样本可能导致错误撤销选举结果；即使证词准确且抽样框误差小，缺少建模假设也常难解决争议。
- 阅读关注点
- 应核对目标总体、证词进入样本的机制、无回应处理，以及检验功效与选区极化、第一类错误之间关系的推导。
- 阅读边界
- 仅据版本未注明的 OpenAlex 索引摘要；具体模型和数值功效未说明，结论不能直接判定某次选举是否存在错误结果。
原文摘要
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).