Bernstein on Legal Corpus Linguistics and the Half Empirical Analysis @Cornell_Law_Rev

Anya Bernstein, SUNY Buffalo Law School, is publishing Legal Corpus Linguistics and the Half Empirical Attitude in volume 106 of the Cornell Law Review (2021). Here is the abstract.

Legal writers have recently turned to corpus linguistics for help interpreting legal texts. Corpus linguistics—a methodology that analyzes large data sets of language use —promises to give empirical grounding to the claims about ordinary language that pervade legal interpretation. Yet, I argue, legal corpus linguistics departs from these empirical origins by ignoring the crucial contexts in which legal language is produced and interpreted. First, legal corpus linguistics ignores the legal context of legal language—conditions, like judicial precedent and statutory co-text, that give legal language authority. So it provides evidence about language use that obscures and misstates the actual issues legal interpreters face. Second, legal corpus linguistics ignores the institutional context of legal language—the way it is produced by certain speakers, taken up by certain audiences, and formulated in particular genres. When legal corpus work treats language as socially undifferentiated, its empirical findings rest on a fictional basis. The underlying problem, I show, is a mismatch of methodology and goal. Corpus linguistics in linguistics makes an empirical claim that its analysis illuminates truths about the language it studies. Legal corpus linguistics, in contrast, uses empirical methods to support a normative claim that its analysis ought to influence our interpretation of legal texts. Treating normative claims as though they were empirical findings constitutes what I call a half-empirical attitude in legal interpretation. At the same time, I suggest ways that legal corpus linguistics could be useful to the production and interpretation of legal texts, as well as to the development of legal theory—if it embraces a more fully empirical attitude. 

 Download the article from SSRN at the link.