Nada Aggadi BA, Kimberley Zeller BS, Tom Busey PhD
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引用次数: 0
Abstract
Forensic firearms and tool mark examiners compare bullets and cartridge cases to assess whether they originate from the same source or different sources. To communicate their observations, they rely on predefined conclusion scales ranging from Identification to Elimination. However, these terms have not been calibrated against the actual strength of the evidence except indirectly through error rate studies. The present research reanalyzes the findings of firearms and cartridge case comparisons from error rate studies to generate a quantitative measure of the strength of the evidence for each comparison. We use an ordered probit model to summarize the distribution of responses of examiners and aggregate the data for all comparisons to produce a set of likelihood ratios. The likelihood ratios can be as low as less than 10, which does not seem to justify the current articulation scale that may imply a strength of evidence of 10,000 or greater. This suggests that examiners are using language that overstates the strength of the evidence by several orders of magnitude.
期刊介绍:
The Journal of Forensic Sciences (JFS) is the official publication of the American Academy of Forensic Sciences (AAFS). It is devoted to the publication of original investigations, observations, scholarly inquiries and reviews in various branches of the forensic sciences. These include anthropology, criminalistics, digital and multimedia sciences, engineering and applied sciences, pathology/biology, psychiatry and behavioral science, jurisprudence, odontology, questioned documents, and toxicology. Similar submissions dealing with forensic aspects of other sciences and the social sciences are also accepted, as are submissions dealing with scientifically sound emerging science disciplines. The content and/or views expressed in the JFS are not necessarily those of the AAFS, the JFS Editorial Board, the organizations with which authors are affiliated, or the publisher of JFS. All manuscript submissions are double-blind peer-reviewed.