On the likelihood of "encapsulating all uncertainty"

This paper is part of the Virtual Special Issue entitled: Measuring and Reporting the Precision of Forensic Likelihood Ratios, [http://www.sciencedirect.com/science/journal/ 13550306/vsi]The assignment of personal probabilities to form a forensic practitioner's likelihood ratio is a mental operation subject to all the frailties of human memory, perception and judgment. While we agree that beliefs expressed as coherent probabilities are neither 'right' nor 'wrong' we argue that debate over this fact obscures both the requirement for and consideration of the 'helpfulness' of practitioner's opinions. We also question the extent to which a likelihood ratio based on personal probabilities can realistically be expected to 'encapsulate all uncertainty'. Courts cannot rigorously assess a forensic practitioner's bare assertions of belief regarding evidential strength. At a minimum, information regarding the uncertainty both within and between the opinions of practitioners is required.Kristy A. Martire, Gary Edmond, Daniel J. Navarro, Ben R. Newel

Finding the perfect match: Fingerprint expertise facilitates statistical learning and visual comparison decision-making

Forensic feature-comparison examiners compare - or "match" - evidence samples (e.g., fingerprints) to provide judgments about the source of the evidence. Research demonstrates that examiners in select disciplines possess expertise in this task by outperforming novices - yet the psychological mechanisms underpinning this expertise are unclear. This article investigates one implicated mechanism: statistical learning, the ability to learn how often things occur in the environment. This ability is likely important in forensic decision-making as samples sharing rarer statistical information are more likely to come from the same source than those sharing more common information. We investigated 46 fingerprint examiners' and 52 novices' statistical learning of fingerprint categories and application of this knowledge in a source-likelihood judgment task. Participants completed four measures of their statistical learning (frequency discrimination judgments, bounded and unbounded frequency estimates, and source-likelihood judgments) before and after familiarization to the "ground-truth" category frequencies. Compared to novices, fingerprint examiners had superior domain-specific statistical learning across all measures - both before and after familiarization. This suggests that fingerprint expertise facilitates domain-specific statistical learning - something that has important theoretical and applied implications for the development of training programs and statistical databases in forensic science