在影响力与新颖性妥协下实现公平投票结果？揭示参与式预算获胜者选举中的偏见
Fair Voting Outcomes with Impact and Novelty Compromises? Unraveling Biases in Electing Participatory Budgeting Winners
AI总结：
针对参与式预算投票缺乏影响力与新颖性评估框架的问题，论文分析345个真实投票结果，揭示 equal shares 在基础设施项目上的影响力损失及福利、教育、文化领域的代表性失衡增益。
摘要：
参与式预算作为民主创新的一种范式，让公民参与将公共预算分配给他们提出并投票支持实施的项目。迄今为止，社会选择文献已经提出并研究了一些投票算法，用于选举受欢迎的项目，而另一些算法则优先考虑选民偏好的比例代表制，例如 equal shares（平等份额）规则。然而，由不同算法选出的获胜项目在更广泛社会中所预期的影响力和新颖性仍完全未被充分探索，既缺乏关于投票影响力的普遍理论，也缺乏用于影响力和新颖性评估的严格统一框架。本文通过从对345个真实投票结果的大规模偏见分析中得出的新颖且引人注目的洞见，应对这一重大挑战，迈向设计有效且公平投票方法的新公理基础；这些结果首次由一套新颖的影响力和新颖性指标组合加以刻画。我们发现强有力的因果证据表明，equal shares 在若干不同成本水平、迄今代表性过高的基础设施项目中伴随着影响力损失。然而，它也在福利、教育和文化方面带来了一种新颖但同样代表性过高的影响力增益。我们讨论了这些结果更广泛的意义，以及如何在竞选设计和项目构思阶段缓解影响力损失。
英文摘要：
Participatory budgeting, as a paradigm for democratic innovations, engages citizens in the distribution of a public budget to projects, which they propose and vote for implementation. So far, voting algorithms have been proposed and studied in social choice literature to elect projects that are popular, while others prioritize on a proportional representation of voters' preferences, for instance, the rule of equal shares. However, the anticipated impact and novelty in the broader society by the winning projects, as selected by different algorithms, remains totally under-explored, lacking both a universal theory of impact for voting and a rigorous unifying framework for impact and novelty assessments. This paper tackles this grand challenge towards new axiomatic foundations for designing effective and fair voting methods. This is via new and striking insights derived from a large-scale analysis of biases over 345 real-world voting outcomes, characterized for the first time by a novel portfolio of impact and novelty metrics. We find strong causal evidence that equal shares comes with impact loss in several infrastructural projects of different cost levels that have been so far over-represented. However, it also comes with a novel, yet over-represented, impact gain in welfare, education and culture. We discuss broader implications of these results and how impact loss can be mitigated at the stage of campaign design and project ideation.
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。
