Abstract
Perpetrator knowledge (also known as “guilty knowledge,” “insider knowledge,” “crime knowledge,” or “first-hand knowledge”) is an important, but undertheorized type of criminal evidence. This article clarifies this concept in several ways. First, it offers a precise, probabilistic definition of what perpetrator knowledge is. Second, the article provides a taxonomy of arguments relating to perpetrator knowledge. This classification is based on an analysis of 438 Dutch criminal cases in which this concept was mentioned. Third, it models these arguments using Bayesian networks. Fourth, the article explains a potential reasoning error relating to perpetrator knowledge, namely the fallacy of appeal to probability.
Original language | English |
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Article number | mgae009 |
Number of pages | 21 |
Journal | Law, Probability and Risk |
Volume | 23 |
Issue number | 1 |
DOIs | |
Publication status | Published - Sept 2024 |
Keywords
- Bayesian networks
- Bayesianism
- criminal proof
- evidence
- perpetrator knowledge