A Bayesian assessment of the probability that the defendant in a criminal trial is guilty depends on the presumed base rate for guilt and the estimated likelihoods of the evidence. This article explores how the base rate shall be determined. Bayesian scholars have recommended a base rate of 1/N, where N is the number of ‘possible perpetrators’, but it is unclear how the reference class of possible perpetrators shall be defined. Several solutions are explored, and it is demonstrated that each solution leads to serious sacrifices in some fundamental principle of criminal justice. Some solutions lead to arbitrary assessments, or assessments that deviate from the facts. Other solutions fail to uphold an acceptable ratio between wrongful acquittals and wrongful convictions. (Less)

中文翻译：

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确定有罪的基本比率

对刑事审判中被告有罪的概率的贝叶斯评估取决于假定的基本有罪率和证据的估计可能性。本文探讨了如何确定基本费率。贝叶斯学者推荐了 1/N 的基本比率，其中 N 是“可能的肇事者”的数量，但尚不清楚如何定义可能的肇事者的参考类别。探索了几种解决方案，并且证明了每种解决方案都会导致刑事司法的某些基本原则的严重牺牲。一些解决方案会导致武断的评估，或偏离事实的评估。其他解决方案未能在错误无罪宣判和错误定罪之间维持可接受的比例。（较少的）