认知大会的最佳规模
The Optimal Size of an Epistemic Congress
摘要：
我们分析了代议制民主国家的国会的最佳规模。我们采取一种认知的观点，选民决定一个二元问题与一个地面真相的结果，每个选民正确地投票，根据他们的能力水平在$[0, 1]$。假设我们可以抽样最好的专家组成一个认知会议，我们发现，最佳的会议规模应该是线性的人口规模。这个结果是惊人的，因为它甚至在允许最高代表以任意高的概率准确时也成立。然后，我们分析了现实世界的数据，发现大会的实际规模远远小于我们的理论结果建议的最佳规模。最后，我们通过分析在什么条件下次优规模的国会仍然优于直接民主，在直接民主中，所有选民投票。
英文摘要：
We analyze the optimal size of a congress in a representative democracy. We take an epistemic view where voters decide on a binary issue with one ground truth outcome, and each voter votes correctly according to their competence levels in $[0, 1]$. Assuming that we can sample the best experts to form an epistemic congress, we find that the optimal congress size should be linear in the population size. This result is striking because it holds even when allowing the top representatives to be accurate with arbitrarily high probabilities. We then analyze real world data, finding that the actual sizes of congresses are much smaller than the optimal size our theoretical results suggest. We conclude by analyzing under what conditions congresses of sub-optimal sizes would still outperform direct democracy, in which all voters vote.
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。
