In many jurisdictions, forensic evidence is presented in the form of categorical statements by forensic experts. Several large-scale performance studies have been performed that report error rates to elucidate the uncertainty associated with such categorical statements. There is growing scientific consensus that the likelihood ratio (LR) framework is the logically correct form of presentation for forensic evidence evaluation. Yet, results from the large-scale performance studies have not been cast in this framework. Here, I show how to straightforwardly calculate an LR for any given categorical statement using data from the performance studies. This number quantifies how much more we should believe the hypothesis of same source vs different source, when provided a particular expert witness statement. LRs are reported for categorical statements resulting from the analysis of latent fingerprints, bloodstain patterns, handwriting, footwear and firearms. The highest LR found for statements of identification was 376 (fingerprints), the lowest found for statements of exclusion was 1/28 (handwriting). The LRs found may be more insightful for those used to this framework than the various error rates reported previously. An additional advantage of using the LR in this way is the relative simplicity; there are no decisions necessary on what error rate to focus on or how to handle inconclusive statements. The values found are closer to 1 than many would have expected. One possible explanation for this mismatch is that we undervalue numerical LRs. Finally, a note of caution: the LR values reported here come from a simple calculation that does not do justice to the nuances of the large-scale studies and their differences to casework, and should be treated as ball-park figures rather than definitive statements on the evidential value of whole forensic scientific fields.
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