Extracting the truth from conflicting eyewitness reports: a formal modeling approach.
Extracting the truth from conflicting eyewitness reports: a formal modeling approach.
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从相互矛盾的目击者报告中提取真相：正式建模方法。
DOI：
10.1037/a0029801
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
D. Bernstein
中科院分区：
文献类型：
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作者：
Berenike Waubert de Puiseau;André Aßfalg;E. Erdfelder;D. Bernstein
目击者经常错误地报告目击犯罪的细节。然而，通常有一个以上的目击者观察犯罪现场。如果是这种情况，一种更准确地重建犯罪细节的方法是汇总各个报告。虽然汇总可能会提高准确性，但提高的程度在很大程度上取决于汇总方法。最简单的方法是多数决原则。这种方法忽略了目击者之间的个体差异，并选择大多数目击者的答案作为正确答案。我们采用了一种基于文化共识理论（CCT）的替代方法，该理论解释了目击者知识的差异。为了测试这种方法的有效性，我们向30名学生展示了2个版本中的1个版本的视频，描述了2个人之间的激烈争吵。这些视频在与关键事件有关的信息量方面存在差异。然后，参与者回答了关于关键事件的问题。基于CCT的分析提供了高度准确的目击者能力估计，反映了视频中可用的信息量。此外，CCT估计导致比多数规则更精确的视频内容重建。对于4至15名目击者的群体来说，这是真实的，对于较大的群体来说，这种差异更加明显。因此，通过同时考虑多个证人的陈述，CCT提供了一种新的方法来评估目击者的准确性，优于标准的信息汇总方法。
Eyewitnesses 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.