Sunde, Nina, Franqueira, Virginia N. L. (2023) Adding transparency to uncertainty: An argument-based method for evaluative opinions. Forensic Science International: Digital Investigation, 47 . Article Number 301657. ISSN 1742-2876. (doi:10.1016/j.fsidi.2023.301657) (KAR id:103353)
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Official URL: https://doi.org/10.1016/j.fsidi.2023.301657 |
Abstract
Over the past 15 years, digital evidence has been identified as a leading cause, or contributing factor, in wrongful convictions in England and Wales. To prevent legal decision-makers from being misled about the relevance and credibility of digital evidence and to ensure a fair administration of justice, adopting a balanced, systematic and transparent approach to evaluating digital evidence and disseminating results is crucial. This paper draws on general concepts from argumentation theory, combined with key principles and concepts from probabilistic and narrative/scenario approaches to develop arguments and analyse evidence. We present the “Argument-Based Method for Evaluative Opinions”, which is a novel method for producing argument-based evaluative opinions in the context of criminal investigation. The method may be used stand-alone or in combination with other qualitative or quantitative/statistical methods to produce evaluative opinions, highlighting the logical relationships between the components making up the argument supporting a hypothesis. To facilitate a structured assessment of the credibility and relevance of the individual argument components, we introduce an Argument Evaluation Scale and, ultimately, an Argument Matrix for a holistic determination of the probative value of the evidence.
Item Type: | Article |
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DOI/Identification number: | 10.1016/j.fsidi.2023.301657 |
Uncontrolled keywords: | Criminal investigations, Evaluative opinion, Digital evidence, Argumentation theory, Practitioners |
Subjects: | Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science |
Divisions: | University-wide institutes > Institute of Cyber Security for Society |
Funders: | University of Kent (https://ror.org/00xkeyj56) |
Depositing User: | Virginia Franqueira |
Date Deposited: | 20 Oct 2023 11:41 UTC |
Last Modified: | 11 Jan 2024 11:11 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/103353 (The current URI for this page, for reference purposes) |
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