Lessons Learned: Navigating a Presidential Election During a Pandemic

2020年的选举不仅可能给寻求候选人和投票程序准确信息的选民带来挑战，也会给致力于管理和保护选举过程的官员、投票工作人员和网络安全专家带来挑战。该奖项支持举办一次研讨会，汇聚了一系列相关领域的专家，讨论从2020年选举中吸取的经验教训。讲习班将探讨我国如何不断改进我们的选举进程，使其在最艰难的时期具有韧性，同时推动对投票进程所有方面的基础科学研究。通过引发学者和实践者之间很少相互接触的长期合作，研讨会将有助于产生新的研究想法和伙伴关系，为未来的选举研究绘制道路。2020年选举带来的各种挑战为跨学科研究提供了强大的机会(例如，政治学、社会学、心理学和信息科学交叉领域的选民行为；选举法、数据科学和网络安全交叉领域的投票机会)。然而，传统的专业协会会议很少能够进行必要的跨学科对话，以全面了解2020年选举的成功和不足。研讨会汇集了来自不同学科的学者，包括法律、政治学、计算机科学、数据科学和数学。研讨会的成果将是一份广泛传播的文件，其中列出了可能导致潜在的NSF DCL征集新提案的新的或更新的研究问题和想法。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The 2020 election has the potential to introduce challenges not only for voters searching for accurate information on candidates and voting procedures, but also for officials, poll workers, and cybersecurity experts working to administer and protect the electoral process. This award supports a workshop bringing together experts from a range of relevant fields to discuss lessons learned from the 2020 election. The workshop will explore how our country can continually improve our electoral process to be resilient in the most trying of times while simultaneously advancing basic scientific research on all aspects of the voting process. By sparking long-term collaboration across scholars and practitioners that rarely engage with one another, the workshop will help generate new research ideas and partnerships that will chart the course for future election research. The myriad challenges posed by 2020 elections provide a strong opportunity for interdisciplinary research (e.g., voter behavior at the intersection of political science, sociology, psychology, and information science; voting access at the intersection of election law, data science, and cybersecurity). However, traditional professional society meetings rarely enable the interdisciplinary dialogue necessary to develop a comprehensive understanding of the successes and shortcomings of the 2020 election. The workshop brings together scholars from across disciplines, including law, political science, computer science, data science, and mathematics. The output from the workshop will be a widely-disseminated document that lays out the new or updated research problems and ideas that could lead to a potential NSF DCL to solicit new proposals.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.