Validation in Forensic Text Comparison: Issues and Opportunities

Author:

Ishihara Shunichi1ORCID,Kulkarni Sonia2,Carne Michael1,Ehrhardt Sabine3,Nini Andrea4ORCID

Affiliation:

1. Speech and Language Laboratory, Australian National University, Canberra, ACT 2601, Australia

2. School of Languages, Literatures, Cultures and Linguistics, Monash University, Clayton, VIC 3800, Australia

3. Bundeskriminalamt, 65173 Wiesbaden, Germany

4. School of Arts, Languages and Cultures, University of Manchester, Manchester M13 9PL, UK

Abstract

It has been argued in forensic science that the empirical validation of a forensic inference system or methodology should be performed by replicating the conditions of the case under investigation and using data relevant to the case. This study demonstrates that the above requirement for validation is also critical in forensic text comparison (FTC); otherwise, the trier-of-fact may be misled for their final decision. Two sets of simulated experiments are performed: one fulfilling the above validation requirement and the other overlooking it, using mismatch in topics as a case study. Likelihood ratios (LRs) are calculated via a Dirichlet-multinomial model, followed by logistic-regression calibration. The derived LRs are assessed by means of the log-likelihood-ratio cost, and they are visualized using Tippett plots. Following the experimental results, this paper also attempts to describe some of the essential research required in FTC by highlighting some central issues and challenges unique to textual evidence. Any deliberations on these issues and challenges will contribute to making a scientifically defensible and demonstrably reliable FTC available.

Funder

an anonymous institution that prefers not to disclose its identity

Publisher

MDPI AG

Subject

Linguistics and Language,Language and Linguistics

Reference73 articles.

1. Who wrote this: Modern forensic authorship analysis as a model for valid forensic science;Ainsworth;Washington University Law Review,2019

2. Aitken, Colin, and Taroni, Franco (2004). Statistics and the Evaluation of Evidence for Forensic Scientists, John Wiley & Sons. [2nd ed.].

3. Aitken, Colin, Roberts, Paul, and Jackson, Graham (2010). Fundamentals of Probability and Statistical Evidence in Criminal Proceedings: Guidance for Judges, Lawyers, Forensic Scientists and Expert Witnesses, Royal Statistical Society. Available online: http://www.rss.org.uk/Images/PDF/influencing-change/rss-fundamentals-probability-statistical-evidence.pdf.

4. Association of Forensic Science Providers (2009). Standards for the formulation of evaluative forensic science expert opinion. Science & Justice, 49, 161–64.

5. Ballantyne, Kaye, Bunford, Joanna, Found, Bryan, Neville, David, Taylor, Duncan, Wevers, Gerhard, and Catoggio, Dean (2022, January 26). An Introductory Guide to Evaluative Reporting. Available online: https://www.anzpaa.org.au/forensic-science/our-work/projects/evaluative-reporting.

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