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arXiv 2211.01249stat.APphysics.soc-ph
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民主政体如何两极分化:多层次视角

How Democracies Polarize: A Multilevel Perspective

Sihao Huang, Alexander F. Siegenfeld, Andrew Gelman

摘要:

民主国家通过各种规模的选举来选择相应级别的行政官员。政治观点的地理分布、下放到每一级的政策问题以及选举之间的多层次互动都可以极大地影响这些代表机构的构成。这种观点并不新鲜:采用联邦制的动机是,联邦制具有单一规模的民主政体所不具备的理想特征。然而,大多数现有的极化模型并没有捕捉到嵌套的地方和国家选举如何与异质的政治地理相互作用。我们首先开发一个框架来描述意见的多级分布,并分析地理尺度之间的方差流,将其应用于美国1912年至2020年的历史数据。我们描述了如何不稳定的选举可能会出现由于空间分布的意见,以及如何权衡国家和地方选举之间发生。我们还研究了多维空间的政治观点,我们表明,在地方显着性的下降可以限制沿选举发生的尺寸,防止联邦制作为一个有效的保障,防止两极分化。这些分析以不同规模的选举和民意分布之间的相互作用为基础,为如何加强民主以缓解两极分化和增加选举代表性提供了见解。

英文摘要:

Democracies employ elections at various scales to select officials at the corresponding levels of administration. The geographical distribution of political opinion, the policy issues delegated to each level, and the multilevel interactions between elections can all greatly impact the makeup of these representative bodies. This perspective is not new: the adoption of federal systems has been motivated by the idea that they possess desirable traits not provided by democracies on a single scale. Yet most existing models of polarization do not capture how nested local and national elections interact with heterogeneous political geographies. We begin by developing a framework to describe the multilevel distribution of opinions and analyze the flow of variance among geographic scales, applying it to historical data in the United States from 1912 to 2020. We describe how unstable elections can arise due to the spatial distribution of opinions and how tradeoffs occur between national and local elections. We also examine multi-dimensional spaces of political opinion, for which we show that a decrease in local salience can constrain the dimensions along which elections occur, preventing a federal system from serving as an effective safeguard against polarization. These analyses, based on the interactions between elections and opinion distributions at various scales, offer insights into how democracies can be strengthened to mitigate polarization and increase electoral representation.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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