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原文連結
論文資訊
- 類型：已發表論文
- 日期：2020
摘要
Recent work in 認知 science has uncovered a 多樣性 of explanatory values, or dimensions along which we judge explanations as better or worse. We propose a 貝氏 account of how these values fit together to guide explanation. The resulting taxonomy provides a set of predictors for which explanations people prefer and shows how core values from psychology, statistics, and the philosophy of science emerge from a common 數學 framework. In addition to operationalizing the explanatory virtues associated with, for example, scientific argument-making, this framework also enables us to reinterpret the explanatory vices that drive conspiracy theories, delusions, and extremist ideologies.
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