To Catch a Thief With and Without Numbers:
Arguments, Scenarios and Probabilities in Evidential Reasoning

Bart Verheij

Mistakes in evidential reasoning can have severe consequences. Especially, errors in the use of statistics have led to serious miscarriages of justice. Fact-finders and forensic experts make errors in reasoning and fail to communicate effectively. As tools to prevent mistakes, three kinds of methods are available. Argumentative methods analyse the arguments and counterarguments that are presented in court. Narrative methods consider the construction and comparison of scenarios of what may have happened. Probabilistic methods show the connections between the probability of hypothetical events and the evidence. Each of the kinds of methods has provided useful normative maxims for good evidential reasoning. Argumentative and narrative methods are especially helpful for the analysis of qualitative information, but do not come with a formal theory that is as well-established as probability theory. In probabilisticmethods, the emphasis is on numeric information, so much so that a standard criticismis that these methods require more numbers than are available. This article offers an integrating perspective on evidential reasoning, combining the strengths of each of the kinds of methods: the adversarial setting of arguments pro and con, the globally coherent perspective provided by scenarios, and the gradual uncertainty of probabilities. In the integrating perspective, arguments and scenarios are interpreted in the quantitative setting of standard probability theory. In this way, the integrated perspective provides a normative framework that bridges the communicative gap between fact-finders and forensic experts. Both qualitative and quantitative information can be used safely, focusing on what is relevant.

Manuscript (in PDF-format)

Verheij, B. (2014). To Catch a Thief With and Without Numbers: Arguments, Scenarios and Probabilities in Evidential Reasoning. Law, Probability and Risk, 13, 307-325. doi:10.1093/lpr/mgu011.

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