More than 100 countries allow people to vote directly on policies in direct democracy elections (e.g., 2016 Brexit referendum). Politicians are often responsible for writing ballot language, and voters frequently encounter ballot measures that are difficult to understand. We examined whether eye movements from a small group of individuals can predict the consequences of ballot language on large-scale voting decisions. Across two preregistered studies (Study 1: N = 120 registered voters, Study 2: N = 120 registered voters), we monitored laboratory participants’ eye movements as they read real ballot measures. We found that eye-movement responses associated with difficulties in language comprehension predicted aggregate voting decisions to abstain from voting and vote against ballot measures in U.S. elections (total number of votes cast = 137,661,232). Eye movements predicted voting decisions beyond what was accounted for by widely used measures of language difficulty. This finding demonstrates a new way of linking eye movements to out-of-sample aggregate-level behaviors.

100 多个国家允许人们在直接民主选举中直接对政策进行投票（例如，2016 年英国脱欧公投）。政治家通常负责编写选票语言，选民经常遇到难以理解的选票措施。我们研究了一小群人的眼球运动是否可以预测投票语言对大规模投票决定的影响。在两项预先注册的研究中（研究 1：N = 120 名注册选民，研究 2：N= 120 名注册选民），我们监测了实验室参与者在阅读真实选票时的眼球运动。我们发现与语言理解困难相关的眼动反应预测了美国选举中弃权和反对投票措施的总投票决定（投票总数 = 137,661,232）。眼球运动预测的投票决定超出了广泛使用的语言难度衡量标准。这一发现展示了一种将眼球运动与样本外聚合水平行为联系起来的新方法。