照亮法医黑匣子研究

IF 1.5 Q2 SOCIAL SCIENCES, MATHEMATICAL METHODS
Kori Khan, A. Carriquiry
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引用次数: 2

摘要

法医学在美国刑事司法系统中起着至关重要的作用。几十年来,许多基于特征的法医学领域,如枪支和工具标记鉴定,在科学界的范围之外发展起来。这些研究的结果被全国的法官广泛依赖。然而,这种依赖是错误的。迄今为止的黑箱研究存在抽样方法不当和高失误率的问题。目前的黑箱研究在得出提交给法院的错误率估计时忽略了这两个问题。我们利用黑箱研究和法庭材料中的可用数据来探讨每种限制的影响。我们表明黑箱研究依赖于非代表性的审查员样本。使用一个流行的弹道学研究的案例研究,我们发现证据表明,这些不具代表性的样本可能比他们来自的更广泛的人群犯更少的错误。我们还发现证据表明,黑箱研究中的缺失是不可忽视的。利用最近一项潜在打印研究的数据,我们表明,忽略这种缺失可能会导致系统地低估错误率。最后,我们提出克服这些限制的具体步骤。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Shining a Light on Forensic Black-Box Studies
Forensic science plays a critical role in the United States criminal justice system. For decades, many feature-based fields of forensic science, such as firearm and toolmark identification, developed outside the scientific community's purview. The results of these studies are widely relied on by judges nationwide. However, this reliance is misplaced. Black-box studies to date suffer from inappropriate sampling methods and high rates of missingness. Current black-box studies ignore both problems in arriving at the error rate estimates presented to courts. We explore the impact of each type of limitation using available data from black-box studies and court materials. We show that black-box studies rely on non-representative samples of examiners. Using a case study of a popular ballistics study, we find evidence that these unrepresentative samples may commit fewer errors than the wider population from which they came. We also find evidence that the missingness in black-box studies is non-ignorable. Using data from a recent latent print study, we show that ignoring this missingness likely results in systematic underestimates of error rates. Finally, we offer concrete steps to overcome these limitations.
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来源期刊
Statistics and Public Policy
Statistics and Public Policy SOCIAL SCIENCES, MATHEMATICAL METHODS-
CiteScore
3.20
自引率
6.20%
发文量
13
审稿时长
32 weeks
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