论文标题

初选中比例排名:一个案例研究

Proportional Ranking in Primary Elections: A Case Study

论文作者

Rosenfeld, Ariel, Shapiro, Ehud, Talmon, Nimrod

论文摘要

许多民主党政党举行初选,这很好地反映了他们的民主性质,并促进了包容性的民主价值。但是,当前用于举行此类主要选举的方法可能不是最合适的,尤其是在需要某种形式的比例排名的情况下。在本文中,我们通过评估每个人使用现实世界数据来实现的,比较了持有原始算法的不同算法方法(即选民投票的不同聚合方法)。特别是,我们通过分析以色列民主党最近举行的主要选举中的现实世界数据来比较六种不同的算法。从技术上讲,我们分析了独特的选民数据并评估通过聚类分析获得的比例性,目的是指出所考虑的每种算法方法下授予不同选民群体的表示形式。我们的发现表明,与所使用的最重要的初选算法(即批准)相反,其他方法(例如顺序比例批准或词尾)可以带来更好的比例排名,因此可能更适合实践中的初选。

Many democratic political parties hold primary elections, which nicely reflects their democratic nature and promote, among other things, the democratic value of inclusiveness. However, the methods currently used for holding such primary elections may not be the most suitable, especially if some form of proportional ranking is desired. In this paper, we compare different algorithmic methods for holding primaries (i.e., different aggregation methods for voters' ballots), by evaluating the degree of proportional ranking that is achieved by each of them using real-world data. In particular, we compare six different algorithms by analyzing real-world data from a recent primary election conducted by the Israeli Democratit party. Technically, we analyze unique voter data and evaluate the proportionality achieved by means of cluster analysis, aiming at pinpointing the representation that is granted to different voter groups under each of the algorithmic methods considered. Our finding suggest that, contrary to the most-prominent primaries algorithm used (i.e., Approval), other methods such as Sequential Proportional Approval or Phragmen can bring about better proportional ranking and thus may be better suited for primary elections in practice.

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