1,721,263 research outputs found
Extracting the truth from conflicting eyewitness reports : A formal modeling approach
No full textEyewitnesses often report details of the witnessed crime incorrectly. However, there is usually more than 1 eyewitness observing a crime scene. If this is the case, one approach to reconstruct the details of a crime more accurately is aggregating across individual reports. Although aggregation likely improves accuracy, the degree of improvement largely depends on the method of aggregation. The most straightforward method is the majority rule. This method ignores individual differences between eyewitnesses and selects the answer shared by most eyewitnesses as being correct. We employ an alternative method based on cultural consensus theory (CCT) that accounts for differences in the eyewitnesses' knowledge. To test the validity of this approach, we showed 30 students 1 of 2 versions of a video depicting a heated quarrel between 2 people. The videos differed in the amount of information pertaining to the critical event. Participants then answered questions about the critical event. Analyses based on CCT rendered highly accurate eyewitness competence estimates that mirrored the amount of information available in the video. Moreover, CCT estimates resulted in a more precise reconstruction of the video content than the majority rule did. This was true for group sizes ranging from 4 to 15 eyewitnesses, with the difference being more pronounced for larger groups. Thus, through simultaneous consideration of multiple witness statements, CCT provides a new approach to the assessment of eyewitness accuracy that outperforms standard methods of information aggregation.Must link to publisher version with DOI ; Article must include the following statement: 'This article may not exactly replicate the final version published in the APA journal. It is not the copy of record.' ; Has correction date for article 07-Jan 2013Peer reviewe
The revelation effect for autobiographical memory : a mixture-model analysis
Full text linkParticipants provided information about their childhood by rating the confidence that they had experienced various events (e.g., 'broke a window playing ball'). On some trials, participants unscrambled a key word from the event-phrase (e.g., wdinwo – window) or an unrelated word (e.g., gnutge – nugget) before seeing the event and giving their confidence rating. Unscrambling led participants to increase their confidence that the event occurred in their childhood, but only when the confidence rating immediately followed the act of unscrambling. This increase in confidence mirrors the “revelation effect” observed in word recognition experiments. We analyze our data using a new signal detection mixture distribution model which does not require that the researcher knows the veracity of memory judgments a priori. Our analysis reveals that unscrambling a key word or an unrelated word affects response bias and discriminability in autobiographical memory tests in ways that are very similar to those that have been previously found for word recognition tasks
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