Hidden Bias in Empirical Textualism

41 Pages Posted: 11 May 2021

See all articles by Matthew Jennejohn

Matthew Jennejohn

Brigham Young University - J. Reuben Clark Law School; European Corporate Governance Institute (ECGI); Johns Hopkins University Applied Physics Laboratory

Samuel Nelson

J. Reuben Clark Law School

D. Carolina Núñez

Brigham Young University - J. Reuben Clark Law School

Date Written: May 10, 2021

Abstract

A new interpretive technique called “corpus linguistics” has exploded in use over the past five years from state supreme courts and federal courts of appeals to the U.S. Supreme Court. Corpus linguistics involves searching a large database, or corpus, of text to identify patterns in the way in which a certain term is used in context. Proponents of the method argue that it is a more “empirical” approach than referencing dictionaries to determine a word’s public meaning, which is a touchstone in originalist approaches to legal interpretation.

This Article identifies an important concern about the use of corpus linguistics in legal interpretation that courts and scholarship have overlooked: bias. Using new machine learning techniques that analyze bias in text, this Article provides empirical evidence that the thousands of documents in the Corpus of Historical American English (COHA), the leading corpus currently used in judicial opinions, reflect gender bias. Courts and scholars have not considered that the COHA is sexist, raising the possibility that corpus linguistics methods could serve as a vehicle for infecting judicial opinions with longstanding prejudices in U.S. society.

In addition to raising this important new problem, this Article charts a course for dealing with it. It explains how hidden biases can be made transparent and introduces steps for “debiasing” corpora used in legal interpretation. More broadly, it shows how the methods introduced here can be used to study biases in all areas of the law, raising the prospect of a revolution in our understanding of how discriminatory biases affect legal decisionmaking.

Keywords: corpus linguistics, textualism, legal interpretation, gender bias

Suggested Citation

Jennejohn, Matthew and Nelson, Samuel and Núñez, D. Carolina, Hidden Bias in Empirical Textualism (May 10, 2021). 109 Georgetown Law Journal 767 (2021), BYU Law Research Paper No. 21-07, Available at SSRN: https://ssrn.com/abstract=3843315

Matthew Jennejohn (Contact Author)

Brigham Young University - J. Reuben Clark Law School ( email )

436 JRCB
Brigham Young University
Provo, UT 84602
United States
9175093028 (Phone)

European Corporate Governance Institute (ECGI) ( email )

c/o the Royal Academies of Belgium
Rue Ducale 1 Hertogsstraat
1000 Brussels
Belgium

Johns Hopkins University Applied Physics Laboratory ( email )

11100 Johns Hopkins Rd
Laurel, MD 20723
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Samuel Nelson

J. Reuben Clark Law School ( email )

430 JRCB
Brigham Young University
Provo, UT 84602
United States

D. Carolina Núñez

Brigham Young University - J. Reuben Clark Law School ( email )

430 JRCB
Brigham Young University
Provo, UT 84602
United States

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