An Aggregation Theory of Character Evidence
47 Pages Posted: 15 Sep 2020 Last revised: 15 Jul 2021
Date Written: July 19, 2020
A central principle of U.S. law is that individuals should be judged in court based on their actions and not on their character. Federal Rule of Evidence 404 therefore prohibits evidence of an individual’s previous actions to prove that the individual acted in accordance with a certain propensity or character. But courts frequently depart from or altogether ignore this rule, resulting in arbitrary judgments based on an individual’s character or prior acts rather than on evidence regarding the events at issue in a case. This raises serious constitutional and fairness concerns, deepens racial and economic inequality in the criminal justice system, and entails a wide range of other harmful effects.
I address this problem from a new angle — a scientific one. I develop a theory of “aggregation evidence” based on principles of estimation and data aggregation in statistics. 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 other-acts character evidence. Based on this analysis, I develop a principled approach to character evidence that accounts for such departures and resolves the uncertainty and arbitrariness surrounding the courts’ current haphazard approach. I then demonstrate broad and significant implications of the proposed framework, including minimizing error in case outcomes and reducing inequality based on race and economic disadvantage in the criminal justice system.
Later versions of this article are available at the following addresses: https://ssrn.com/abstract=3883017.https://ssrn.com/abstract=3883579.
Suggested Citation: Suggested Citation