Dr Emmanuel Nsiah Amoako Emmanuel.Nsiahamoako@uwe.ac.uk
Senior Lecturer in Forensic Science
Admissibility of forensic evidence and expert witnesses
Nsiah Amoako, Emmanuel
Authors
Abstract
In GBVAW cases, where forensic evidence will likely form part of the evidence for the prosecution, an expert in the specific evidence type (such as a DNA expert) will be required to assess the evidence in the context of the case to help the court decide some materials of facts in determining the guilt or innocence of the accused. Available published literature continues to demonstrate the adverse implications of unreliable forensic evidence and experts (or those who claim to be one) and their reports and testimonies (Chapter 11) on criminal convictions. In fact, in countries with advanced forensic science practice and criminal justice procedures, such as the USA, UK, and Australia, the misinterpretation of the value of scientific evidence is one of the major contributing factors to the so-called forensically-caused wrongful convictions. Drawing
references to case laws in South Africa, England and Wales, and the United States, this chapter reviews procedures currently in place to guide and assist the court or trier of fact in their dealings with and admission of forensic evidence and experts as witnesses in cases.
Publication Date | 2024-05 |
---|---|
Deposit Date | May 31, 2024 |
Pages | 91-96 |
Book Title | Forensic Evidence Processing in Gender-Based Violence Cases: Handbook for Criminal Justice Practitioners |
Chapter Number | 10 |
Public URL | https://uwe-repository.worktribe.com/output/12012776 |
Publisher URL | https://www.unodc.org/rosaf/uploads/documents/Publication/13.5.2024_Forensic_Evidence_Processing_in_Gender-Based_Violence_Cases.pdf |
You might also like
Written evidence from Dr Emmanuel Nsiah Amoako (UKR0065)
(2023)
Preprint / Working Paper
The UK forensic science regulator: Fit for purpose?
(2021)
Journal Article
Downloadable Citations
About UWE Bristol Research Repository
Administrator e-mail: repository@uwe.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search