裸统计证据的推理性质与规范法理

The Inferential Nature and Normative Jurisprudence of Naked Statistical Evidence

裸统计证据发挥证明作用的方式,是将某个具体的个人或事件归入一类人或一类事件,然后指出该类人或事件在整体上具有某个盖然性特征,从而证明这个具体个人或事件具有该特征或做出了某个行为。裸统计证据可以证明一个极高的概率值。如果将司法证明的盖然性理解为帕斯卡模式意义上的概率性,那么裸统计证据能够满足法定的证明要求。然而,建立在帕斯卡概率基础上的概率命题观点和部分信念观点,无法解释和解决裸统计证据的推理悖论。绝对信念观点则认为,仅根据裸统计证据,一位理性的事实认定者无法形成对于案件事实的合理信念。绝对信念观点以培根概率模式解释司法证明的盖然性,认为信念必须建立在有“分量”的证据基础上。于是,裸统计证据尽管指示了极高的概率值,但是缺乏证据的应有分量。只有“个别化”的证据才能“涵盖”作为具体事件的案件事实,裸统计证据和待证事实之间存在巨大的“信息空隙”,远未达到法定的证明要求。裸统计证据不仅自身无法满足充分性要求,它还可能引发证据推理合法性欠缺、不公正的偏见、概率计算错误、证据信息的不平等利用等问题。因此,证据立法或司法实践需要谨慎对待裸统计证据的采纳与排除。

Naked statistical evidence applies to a case by affiliating a specific person or event to a general category of people or events,which as a whole has a certain probability characteristic,thus proving that the specific person or event has that characteristic or has performed a certain act.It can prove an extremely high probability value.If probability in judicial proof were interpreted as probability in Pascalian mode,naked statistical evidence could satisfy the legal requirements for proof.Based on the Pascalian probability,views of probabilistic proposition and partial belief cannot explain or solve proof paradoxes of naked statistical evidence.Categorical belief theory holds that a rational fact finder is unable to form a reasonable belief about the facts of a case merely on the ground of statistical evidence.It explains the probability of judicial proof under the Baconian approach,and asserts that belief must be built on the evidential foundation with“weight”.Naked statistical evidence,although indicating a high probability value,lacks the weight of evidence.It is only the“individualized”evidence that can“cover”the facts of a case as specific events.There are huge“information voids”between naked statistical evidence and the facts to be proved,thus the former is far from meeting the legal requirements for proof.Naked statistical evidence fail to fulfill the sufficiency requirement on its own and may also lead to problems such as lack of legitimacy of evidential reasoning,unfair prejudices,miscalculation of probabilities,as well as unequal access to evidential information.Hence,both legislators and courts need to be cautious when it comes to admitting and excluding naked statistical evidence.