论文标题
通过计算参与式选举的多种代表性 - 案例研究的教训
Diverse Representation via Computational Participatory Elections -- Lessons from a Case Study
论文作者
论文摘要
选举是民主进程的中央机构,在公共或私人治理中,选举通常是个人委员会。为了确保当选机构的合法性,选举过程应确保代表不同的群体,特别是由于性别,种族或其他社会显着属性而被边缘化的群体成员。为了应对这一代表挑战,我们设计了一个新颖的参与性选举过程,在计算系统的支持下实施了代表协议。该过程明确使选民能够在第一轮中灵活地决定代表性标准,然后让他们在第二轮中投票选出候选人。在两轮比赛之后,采用了计数方法,该方法选择了候选人委员会,该委员会最大程度地提高了第二轮中获得的选票数量,以满足第一轮中提供的标准为条件。借助瑞士96名代表的初选中应用此过程的详细用例,我们解释了这种方法如何通过实现更好的“描述性代表”来促进政治选举中的公平性。此外,基于此用例,我们确定了所学到的经验教训,这些教训适用于社会或政治环境中使用的参与式计算系统。确定并提出了良好的实践。
Elections are the central institution of democratic processes, and often the elected body -- in either public or private governance -- is a committee of individuals. To ensure the legitimacy of elected bodies, the electoral processes should guarantee that diverse groups are represented, in particular members of groups that are marginalized due to gender, ethnicity, or other socially salient attributes. To address this challenge of representation, we have designed a novel participatory electoral process coined the Representation Pact, implemented with the support of a computational system. That process explicitly enables voters to flexibly decide on representation criteria in a first round, and then lets them vote for candidates in a second round. After the two rounds, a counting method is applied, which selects the committee of candidates that maximizes the number of votes received in the second round, conditioned on satisfying the criteria provided in the first round. With the help of a detailed use case that applied this process in a primary election of 96 representatives in Switzerland, we explain how this method contributes to fairness in political elections by achieving a better "descriptive representation". Further, based on this use case, we identify lessons learnt that are applicable to participatory computational systems used in societal or political contexts. Good practices are identified and presented.