ABSTRACT
A photo lineup, which is a cross between an old/new and a forced-choice recognition memory test, consists of one suspect, whose face was either seen before or not, and several physically similar fillers. First, the participant/witness must decide whether the person who was previously seen is present (old/new) and then, if present, choose the previously seen target (forced choice). Competing signal-detection models of eyewitness identification performance make different predictions about how certain variables will affect a witness's ability to discriminate previously seen (guilty) suspects from new (innocent) suspects. One key variable is the similarity of the fillers to the suspect in the lineup, and another key variable is the size of the lineup (i.e., the number of fillers). Previous research investigating the role of filler similarity has supported one model, known as the Ensemble model, whereas previous research investigating the role of lineup size has supported a competing model, known as the Independent Observations model. We simultaneously manipulated these two variables (filler similarity and lineup size) and found a pattern that is not predicted by either model. When the fillers were highly similar to the suspect, increasing lineup size reduced discriminability, but when the fillers were dissimilar to the suspect, increasing lineup size enhanced discriminability. The results suggest that each additional filler adds noise to the decision-making process and that this noise factor is minimized by maximizing filler dissimilarity. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
ABSTRACT
Police investigators worldwide use lineups to test an eyewitness's memory of a perpetrator. A typical lineup consists of one suspect (who is innocent or guilty) plus five or more fillers who resemble the suspect and who are known to be innocent. Although eyewitness identification decisions were once biased by police pressure and poorly constructed lineups, decades of social science research led to the development of reformed lineup procedures that provide a more objective test memory. Under these improved testing conditions, cognitive models of memory can be used to better understand and ideally enhance eyewitness identification performance. In this regard, one question that has bedeviled the field for decades is how similar the lineup fillers should be to the suspect to optimize performance. Here, we model the effects of manipulating filler similarity to better understand why such manipulations have the intriguing effects they do. Our findings suggest that witnesses rely on a decision variable consisting of the degree to which the memory signal for a particular face in the lineup stands out relative to the crowd of memory signals generated by the set of faces in the lineup. The use of that decision variable helps to explain why discriminability is maximized by choosing fillers that match the suspect on basic facial features typically described by the eyewitness (e.g., age, race, gender) but who otherwise are maximally dissimilar to the suspect. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
