The Use of Corpus Linguistics in Legal Interpretation

Annual Review of Linguistics. 2021. 7:473–91

Posted: 14 Jul 2020 Last revised: 25 Jan 2021

Multiple version iconThere are 2 versions of this paper

Date Written: June 19, 2020


Download link (see use restrictions after Abstract):

Over the past decade, the idea of using corpus linguistics in legal interpretation has attracted interest on the part of judges, lawyers, and legal academics in the United States. This paper provides an introduction to this nascent movement, which is generally referred to as “Law and Corpus Linguistics” or “LCL”. After briefly summarizing LCL’s origin and development, we will situate LCL within legal interpretation, by discussing the legal concept of “ordinary meaning,” which establishes the framework within which LCL operates, and within linguistics, by identifying the subfields that are most relevant to LCL. We will then offer a linguistic justification for an idea that is implicit in the case law and that provides important support for using corpus analysis in legal interpretation: that data about patterns of usage provides evidence of how words and other expressions are ordinarily understood. We go on to discuss linguistic issues arising from the use of corpus linguistics in dealing with disputes involving lexical ambiguity and categorization. The paper concludes by pointing out some challenges that the growth of LCL will present for both legal professionals and linguists.

This paper is copyrighted and may be downloaded only for personal use. Any further/multiple distribution, publication, or commercial usage requires submission of a permission request addressed to the Copyright Clearance Center (

Keywords: corpus linguistics, legal interpretation, lexicography, cognitive linguistics, lexical semantics, categorization

Suggested Citation

Goldfarb, Neal, The Use of Corpus Linguistics in Legal Interpretation (June 19, 2020). Annual Review of Linguistics. 2021. 7:473–91, Available at SSRN:

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Abstract Views
PlumX Metrics