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MODELLING INDIVIDUAL EXPERTISE IN GROUP JUDGEMENTS

机译:在小组评判中建模个人专家

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摘要

Group judgements are often - implicitly or explicitly - influenced by their members' individual expertise. However, given that expertise is seldom recognized fully and that some distortions may occur (bias, correlation, etc.), it is not clear that differential weighting is an epistemically advantageous strategy with respect to straight averaging. Our paper characterizes a wide set of conditions under which differential weighting outperforms straight averaging and embeds the results into the multidisciplinary group decision-making literature.
机译:集体判断通常(隐式或显式)受其成员个人专长的影响。但是,由于很少充分认识到专业知识,并且可能会发生一些失真(偏差,相关性等),因此相对于直接平均,差分加权在认识上是有利的策略尚不清楚。我们的论文描述了一系列条件,在这些条件下,差分加权的表现优于直接平均,并将结果嵌入多学科小组决策文献中。

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