刑事证明标准的高概率模型

High Probability Model of the Criminal Standard of Proof

在刑事司法证明中,为了实现司法审判的数字化,有必要对刑事证明标准进行量化描述。法律概率主义通过有罪概率和概率阈值构建了“高概率裁决模型”。根据这一模型,当有罪概率是准确的高概率时,裁决应当认定被告有罪。但是,该模型受到法律传统主义的强烈批判,认为用高概率来描述刑事证明标准在道德上不可接受且会产生推理悖论,而我们将通过对刑事证明标准的重构为其进行辩护。刑事证明标准可细分为叙事性、稳定性、完全性和充分性四要素。当审判满足叙事性、稳定性和完全性时,有罪概率的准确性得以确保。如果此时的有罪概率还满足充分性,则可以认为审判满足刑事证明标准,并应认定被告有罪。因此,一旦有罪概率的准确性得到保障,刑事证明标准可以化归为高概率。高概率裁决模型具有正当性,能消解传统主义的批判,促使审判实现核心功能。

In criminal justice proof,in order to achieve the digitization of judicial trials,it is necessary to quantify the criminal standard of proof.Legal probabilism constructs the“high probability decision model”through the guilty probability and probability threshold.According to this model,when the guilt probability is accurate high probability,the verdict should find the defendant guilty.But,this model has been strongly criticized by legal traditionalists,who argue that it is morally unacceptable to describe the criminal standard of proof with high probability and it will lead to reasoning paradoxes.However,we will defend this model by reconstructing the criminal standard of proof.The criminal standard of proof can be divided into four-fold elements:narrativity,stability,completeness and sufficiency.When a trial satisfies narrativity,stability and completeness,the accuracy of the guilt probability is ensured.If the guilt probability further satisfies sufficiency at this time,then the trial should be considered to meet the criminal standard of proof and the defendant should be found guilty.Therefore,once the accuracy of the guilt probability is guaranteed,the criminal standard of proof can be reduced to a high probability.The high probability decision model has justification and can dispel the criticisms of traditionalism,and can also promote the core function of trials.