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The Value of Performance Weights and Discussion in Aggregated Expert Judgments

机译：绩效权重的价值和专家评审中的讨论

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摘要

In risky situations characterized by imminent decisions, scarce resources, and insufficient data, policymakers rely on experts to estimate model parameters and their associated uncertainties. Different elicitation and aggregation methods can vary substantially in their efficacy and robustness. While it is generally agreed that biases in expert judgments can be mitigated using structured elicitations involving groups rather than individuals, there is still some disagreement about how to best elicit and aggregate judgments. This mostly concerns the merits of using performance-based weighting schemes to combine judgments of different individuals (rather than assigning equal weights to individual experts), and the way that interaction between experts should be handled. This article aims to contribute to, and complement, the ongoing discussion on these topics.
机译：在以迫在眉睫的决策，稀缺的资源和不足的数据为特征的危险情况下，决策者需要依靠专家来估计模型参数及其相关的不确定性。不同的激发和聚集方法在功效和鲁棒性方面可以有很大不同。虽然普遍认为，可以通过使用涉及群体而不是个人的结构化启发来减轻专家判断中的偏见，但对于如何最佳地得出和汇总判断仍存在一些分歧。这主要涉及使用基于绩效的加权方案来组合不同个人的判断的优点（而不是给各个专家分配相同的权重），以及专家之间的交互方式。本文旨在促进和补充有关这些主题的持续讨论。

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