摘要
有大量文献抒发了法律对统计/概率证据的厌烦,尤其是对裸统计证据的排斥.这类文献都是基于错误的前提才持有这样的态度.至少就美国法律而言,人们对统计形式的证明并没有普遍反感,当证据的提供满足了可采性(其中最重要的是可靠性)正常标准时,即使裸统计数据也是可采的,并足以支持裁决.相反的信念是建立在一系列差错基础上的:最重要的是,对法律制度的结构和普通法裁决性质的错误建模.造成这些错误的原因是,这些文献常见的方法论依赖于奇怪的假设,这些假设错误模拟了潜在法律关系,并包含了不可能的认识论要求.总的来说,这些现象分散了人们对影响法律制度的真问题的注意力.
Abstract
A vast literature has developed probing the law's aversion to statistical/probability evidence in general and its rejection of naked statistical evidence in particular.This literature rests on false premises.At least so far as US law is concerned,there is no general aversion to statistical forms of proof and even naked statistics are admissible and sufficient for a verdict when the evidentiary proffer meets the normal standards of admissibility,the most important of which is reliability.The belief to the contrary rests upon a series of mistakes:most importantly,mismodeling of the structure of legal systems and the nature of common law decision-making.Contributing to these mistakes is the common methodology in this literature of relying on weird hypotheticals that mismodel the underlying legal relations and contain impossible epistemological demands.Collectively,these phenomena have distracted attention from issues that actually affect real legal systems.
NETL
NSTL
万方数据