How Police Officers Construct Lineups: A National Survey

Abstract

In criminal investigations, considerable weight is given to eyewitness identification evidence. In some cases, like assault and robbery, this evidence may be the only kind available. Over the last two decades, considerable research has been aimed at the factors that cause identification errors. However, virtually all of this work has involved undergraduates and naive lay persons as subjects. There is little known on what police officers do in the course of their work. The present research investigates the procedures that police investigators employ when they construct live and photographic lineups. Surveys were sent to 500 U.S. police jurisdictions along with a cover letter requesting that it be completed by the person most experienced in constructing lineups; 220 were returned. On average, the respondents had 12 years experience as police officers and had constructed a mean of 329 lineups (89 live, 240 photographic). For many items, the results were consistent with those of previous laboratory research. For example, the police officers reported giving more attention to upper face features (e.g., hair) in selecting non-suspect lineup members (foils) which is consistent with research on feature saliency. However, other results indicate that the police use different procedures than those recommended in the research literature. For example, the police officers report using similarity as the major basis for selecting the nonsuspects (foils), whereas, research shows that selection of foils based exclusively on suspect appearance can produce biased lineups. In addition, there is considerable research showing that sequential lineups are more fair than simultaneous lineups, yet only 40% of the police investigators reported having used the sequential technique. These and other findings provide direction and implications for research opportunities. It is concluded that systematic investigation of actual police procedures is a more direct approach of studying ways to decrease identification errors.

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