An Aggregation Theory of Character Evidence

Abstract

Courts frequently depart from Federal Rule of Evidence 404, which prohibits evidence of a person’s prior acts to prove that the person acted according to a certain character or propensity. This leads to verdicts that are unpredictable and based on behavior not at issue in a case. I develop a theory of “aggregation evidence,” which draws on principles of estimation and data aggregation in statistics and ties together evidence from a broad range of contexts. I apply this theory to analyze the effects of character evidence on accuracy, and to understand why and when courts depart from the rule against character evidence. I show that a type of character evidence that I call “objective-chance evidence” stands apart from other forms of character evidence in its ability to improve accuracy. I then argue that a formal exception for this type of evidence may hold the key to a more coherent rule.

An earlier version of this article can be found at the following address on the author page at the following address: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3664837.

Keywords: character evidence, Rule 404, Federal Rules of Evidence, FRE, doctrine of chances, prior-acts evidence, other-acts evidence, propensity evidence, doctrine of objective chances, judgment variability, unpredictability, accuracy, bias-variance tradeoff, shrinkage estimation, hierarchical model