Statistical evidence and the criminal verdict asymmetry

Author:

Fried Avital

Abstract

AbstractEpistemologists have posed the following puzzle, known as the proof paradox: Why is it intuitively problematic for juries to convict on the basis of statistical evidence and yet intuitively unproblematic for juries to convict on the basis of far less reliable, non-statistical evidence? To answer this question, theorists have explained the exclusion of statistical evidence by arguing that legal proof requires certain epistemic features. In this paper, I make two contributions to the debate. First, I establish the Criminal Verdict Asymmetry, a previously-unarticulated asymmetry between the epistemic norms of guilty and not guilty verdicts. I argue that the prosecution and defense’s different epistemic burdens influence whether statistical evidence can generate the type of verdict each side pursues. Second, I point out a mistake in how theorists have understood the role of statistical evidence in criminal trials. Though epistemologists have primarily focused on whether statistical evidence can generate specific epistemic features required for convictions, I consider whether statistical evidence can demonstrate a lack of such features. I find that there are epistemic advantages to allowing the defense to introduce statistical evidence which can reveal the prosecution’s failure to prove the defendant’s guilt.

Publisher

Springer Science and Business Media LLC

Subject

General Social Sciences,Philosophy

Reference55 articles.

1. Abshire, J., & Bornstein, B. H. (2003). Juror sensitivity to the cross-race effect. Law and Human Behavior, 27(5), 471–480. https://doi.org/10.1023/A:1025481905861

2. Agathocleus, A. (2020). How eyewitness misidentification can send innocent people to prison, innocence project. Retrieved May 24, 2021from https://innocenceproject.org/how-eyewitness-misidentification-can-send-innocent-people-to-prison/

3. Allen, R. J. (1990). On the significance of batting averages and strikeout totals: A clarification of the naked statistical evidence debate, the meaning of evidence, and the requirement of proof beyond a reasonable doubt. Tulane Law Review, 65, 1093–1110.

4. Blome-Tillmann, M. (2015). ‘Sensitivity, causality, and statistical evidence in courts of law. Thought: A Journal of Philosophy, 4(2), 102–112. https://doi.org/10.1002/tht3.163

5. Blome-Tillmann, M. (2017). “More Likely Than Not”: Knowledge first and the role of statistical evidence in courts of law. In A. Carter, E. Gordon, & B. Jarvis (Eds.), Knowledge first: Approaches in epistemology and mind (pp. 278–292). Oxford University Press.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3