Faculty Journal Articles and Book Chapters

ORCID (Links to author’s additional scholarship at ORCID.org)

https://orcid.org/0000-0003-4888-2842

Abstract

A central principle of U.S. law is that individuals should be judged in court based on their actions and not on their character. Rule 404 of the Federal Rules of Evidence therefore prohibits evidence of an individual’s previous acts to prove that the individual acted in accordance with a certain character or propensity. But courts regularly deviate from or altogether ignore this rule, resulting in arbitrariness and judgments based on an individual's prior acts rather than on evidence regarding the events at issue in a case.

In this Article, I argue that at the center of the unpredictability surrounding the rule against character evidence is a type of evidence that I refer to as “objective-chance evidence”--that is, evidence regarding other events of the same general kind as the event in question, offered to show that the event in question is due to some intent or design rather than to accident or chance. I apply simple scientific principles of information aggregation to examine the nature of objective-chance evidence in the courts and literature. I then argue that central to a more logical and effective approach to character evidence are 1) a proper understanding of objective-chance evidence as a particular category of character evidence, and 2) an “objective-chance exception” that replaces the rule against character evidence with a Rule 403 balancing for objective-chance evidence. I show that these conditions may permit a more coherent interpretation of Rule 404 and ultimately a stricter adherence to the rule against character evidence.

Publication Title

Alabama Law Review

Document Type

Article

Keywords

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

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