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A Bayesian truth serum for subjective data.

作者信息

Prelec Drazen

机构信息

Massachusetts Institute of Technology, Sloan School of Management, E56-320, 38 Memorial Drive, Cambridge, MA 02139, USA.

出版信息

Science. 2004 Oct 15;306(5695):462-6. doi: 10.1126/science.1102081.

DOI:10.1126/science.1102081
PMID:15486294
Abstract

Subjective judgments, an essential information source for science and policy, are problematic because there are no public criteria for assessing judgmental truthfulness. I present a scoring method for eliciting truthful subjective data in situations where objective truth is unknowable. The method assigns high scores not to the most common answers but to the answers that are more common than collectively predicted, with predictions drawn from the same population. This simple adjustment in the scoring criterion removes all bias in favor of consensus: Truthful answers maximize expected score even for respondents who believe that their answer represents a minority view.

摘要

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