Decisions made during forensic investigations are commonly based on personal knowledge, experiences and assumptions. However, forensic professionals generally do not receive feedback on the outcomes of their decisions, resulting in a deficient learning system. An imperfect individual knowledge base can lead to suboptimal decisions without professionals in the criminal justice chain being aware of it. In practice, this has led to considerable variation and lack of well-founded knowledge in the first phases of the forensic investigation process.The desired situation is that forensic professionals can make decisions based on substantiated knowledge, with transparency about the choices made, so that these decisions can be reflected upon by themselves and other actors in the criminal justice process.The aim of the project is to develop an interactive decision support tool that can assist complex decision-making within the forensic domain. This support tool can enable crime scene investigators to access and utilize data on historic cases, supplemented with results from scientific research. This knowledge can help address questions related to the likelihood of obtaining a DNA profile and its relevance to the crime. In this way, the crime scene investigation will become 'experience-and-evidence-based', meaning that both the valuable experience of crime scene investigators and the rich scientific knowledge derived from historical case data and experiments can be taken into account when making decisions.
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Criminal expertise plays a crucial role in the choices offenders make when committing a crime, including their modus operandi. However, our knowledge about criminal decision making online remains limited. Drawing on insights from cyber security, we conceptualize the cybercrime commission process as the sequence of phases of the cyber kill chain that offenders go through. We assume that offenders who follow the sequence consecutively use the most efficient hacking method. Building upon the expertise paradigm, we hypothesize that participants with greater hacking experience and IT skills undertake more efficient hacks. To test this hypothesis, we analyzed data from 69 computer security and software engineering students who were invited to hack a vulnerable website in a computer lab equipped with monitoring software, which allowed to collect objective behavioral measures. Additionally, we collected individual measures regarding hacking expertise through an online questionnaire. After quantitatively measuring efficiency using sequence analysis, a regression model showed that the expertise paradigm may also apply to hackers. We discuss the implications of our novel research for the study of offender decision-making processes more broadly.
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In this thesis several studies are presented that have targeted decision making about case management plans in probation. In a case management plan probation officers describe the goals and interventions that should help offenders stop reoffending, and the specific measures necessary to reduce acute risks of recidivism and harm. Such a plan is embedded in a judicial framework, a sanction or advice about the sanction in which these interventions and measures should be executed. The topic of this thesis is the use of structured decision support, and the question is if this can improve decision making about case management plans in probation and subsequently improve the effectiveness of offender supervision. In this chapter we first sketch why structured decision making was introduced in the Dutch probation services. Next we describe the instrument for risk and needs assessment as well as the procedure to develop case management plans that are used by the Dutch probation services and that are investigated in this thesis. Then we describe the setting of the studies and the research questions, and we conclude with an overview of this thesis.
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