The Negative Effect Fallacy: A Case Study of Incorrect Statistical Reasoning by Federal Courts

Ryan D. Enos, Anthony Fowler, Christopher S. Havasy

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

This article examines the negative effect fallacy, a flawed statistical argument first utilized by the Warren Court in Elkins v. United States. The Court argued that empirical evidence could not determine whether the exclusionary rule prevents future illegal searches and seizures because “it is never easy to prove a negative,” inappropriately conflating the philosophical and arithmetic definitions of the word negative. Subsequently, the Court has repeated this mistake in other domains, including free speech, voting rights, and campaign finance. The fallacy has also proliferated into the federal circuit and district court levels. Narrowly, our investigation aims to eradicate the use of the negative effect fallacy in federal courts. More broadly, we highlight several challenges and concerns with the increasing use of statistical reasoning in court decisions. As courts continue to evaluate statistical and empirical questions, we recommend that they evaluate the evidence on its own merit rather than relying on convenient arguments embedded in precedent.

Original languageEnglish (US)
Pages (from-to)618-647
Number of pages30
JournalJournal of Empirical Legal Studies
Volume14
Issue number3
DOIs
StatePublished - Sep 2017

All Science Journal Classification (ASJC) codes

  • Education
  • Law

Fingerprint

Dive into the research topics of 'The Negative Effect Fallacy: A Case Study of Incorrect Statistical Reasoning by Federal Courts'. Together they form a unique fingerprint.

Cite this