Université Catholique de Louvain, Belgium.
International Centre for Comparative Criminology, Canada; Simon Fraser University, Canada; Laval University, Canada.
Forensic Sci Int. 2022 Nov;340:111446. doi: 10.1016/j.forsciint.2022.111446. Epub 2022 Sep 5.
The focus of the current study is to examine the collection and analysis of traces that are related to crime scene behaviors in sexual homicide cases as well as the factors influencing the solving of these crimes. Using 230 sexual homicide cases from the SHielD database, we computed two neural network models based on the multi-layer perceptron algorithm. First, we determined whether certain crime scene characteristics predicted the collection and analysis of traces (dependent variable for Model 1). Not surprisingly, the results indicate that trace collection and analysis were more likely to occur in sexual homicide cases with crime scene behaviors exhibiting the highest risk for trace transfer (e.g. close interactions with the victim) as well as the best conditions for trace persistence (e.g. body is found indoors). Situational and physical aspects of the crime scene are thus taken into account when deciding on the collection and analysis of traces. Second, we examined the situations in which the collection and analysis of traces contributes to crime solving (dependent variable for Model 2). The results suggest that the collection and analysis of traces does not necessarily predict the resolution of the case. Specifically, the analyses show that the collection and analysis of traces is useful for crime solving when: (1) the offenders' behaviors increase the opportunities for leaving traces at the crime scene, and (2) when the environmental and temporal aspects are favorable to the collection of traces. The impact of trace collection and analysis on case resolution is thus depending on the context of the case. Furthermore, the subsequent steps, such as the result of the trace analysis, the introduction into a database, the obtention of a result from this comparison, etc. might also affect case resolution, and thus interfere in the link between trace collection and analysis and case resolution.
本研究的重点是检验与性杀人案件中犯罪现场行为相关的痕迹收集和分析,以及影响这些犯罪案件解决的因素。我们使用 SHielD 数据库中的 230 个性杀人案件,基于多层感知器算法计算了两个神经网络模型。首先,我们确定了某些犯罪现场特征是否可以预测痕迹的收集和分析(模型 1 的因变量)。不出所料,结果表明,在犯罪现场行为表现出最高痕迹转移风险(例如与受害者的密切互动)以及最佳痕迹持续条件(例如尸体在室内发现)的性杀人案件中,更有可能进行痕迹收集和分析。因此,在决定收集和分析痕迹时,会考虑犯罪现场的情境和物理方面。其次,我们研究了收集和分析痕迹有助于破案的情况(模型 2 的因变量)。结果表明,收集和分析痕迹不一定能预测案件的解决。具体来说,分析表明,当以下情况发生时,收集和分析痕迹对破案有用:(1)犯罪者的行为增加了在犯罪现场留下痕迹的机会,(2)环境和时间方面有利于痕迹的收集。因此,痕迹收集和分析对案件解决的影响取决于案件的背景。此外,后续步骤,如痕迹分析的结果、引入数据库、从该比较中获得结果等,也可能影响案件的解决,从而干扰痕迹收集和分析与案件解决之间的联系。