Bridging the gap between Bayesian and story-comparison models of juridical inference

Abstract

Abstract In this article, I offer a survey and critique of the long-standing debate within evidence scholarship over what descriptive model best captures the manner in which judges and juries determine disputed facts. For decades, there has been a stand-off between Bayesians, who believe that the task of fact-finding can best be understood in probabilistic terms, and story-model proponents, who describe the task of fact-finding in terms of comparative evaluation of competing stories. Drawing on the dual-process tradition in psychology and cognitive science research, I argue that committing to either view on its own fails to capture important aspects of the fact-finding process. The dual-process tradition predicts that judges and juries typically process a great volume of information in an automatic and unconscious way that bears a closer resemblance to the dense networks of conditional probability relations envisioned by Bayesians than to the linear comparisons of separate, hypothetical stories. At the same time, however, fact-finders sometimes engage a second layer of conscious, semantically based reasoning that does involve explicit story-comparison. Sometimes such reasoning is used to channel or override the intuitions that flow from the first stage of reasoning, but at other times it will work instead to justify or defend such intuitions from outside attack. This dual-process account has important implications for the debate between Bayesian and story-model approaches, making it more likely that components of both are necessary to fully appreciate the task of fact-finding.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 13 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.