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Using confidence ratings to identify a target among foils
Authors:James D. Sauer  Neil Brewer  Nathan Weber
Affiliation:1. Institut de Neurosciences de la Timone UMR 7289 Aix-Marseille Université, CNRS Faculté de Médecine, 27 boulevard Jean Moulin, Marseille 13005, France;2. Laboratoire d’Informatique et Systèmes UMR 7020 Aix-Marseille Université, CNRS, Ecole Centrale de Marseille Faculté des Sciences, 163 avenue de Luminy, Case 901, Marseille 13009, France
Abstract:Sauer, Brewer, and Weber (2008) advanced a novel procedure for testing eyewitness recognition memory. Rather than providing a single decision (i.e., identifying a lineup member or rejecting the lineup as a whole), participants rated their confidence that each lineup member was the culprit. Classification algorithms determined when patterns of confidence ratings indicated suspect guilt or innocence. Across varied test stimuli, confidence-based classifications equalled or out-performed single decisions. However, Sauer et al.’s classification criteria were designed to optimize performance for the data to which they were applied. If effective classification using confidence ratings requires such idiosyncratic criteria, the applied utility of the confidence procedure is nil. We re-analysed the data from Sauer et al.’s two identification experiments and demonstrated that confidence-based classification performance exceeding that of a traditional lineup task did not depend on uniquely developed classification criteria. Confidence-rating lineups offer a potentially promising alternative to procedures requiring single decisions from witnesses.
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