How do people reason in the face of complex and contradictory evidence? Focusing on investigative and legal contexts, we present an idiom-based approach to evidential reasoning, in which people combine and reuse causal schemas to capture large bodies of interrelated evidence and hypotheses. We examine both the normative and descriptive status of this framework, illustrating with real legal cases and empirical studies. We also argue that it is qualitative casual reasoning, rather than fully Bayesian computation, that lies at the heart of human evidential reasoning.
© 2017 K. Schulz