Hypothesis Testing Ordinary Meaning

Corpus linguistic tools promise to make determinations of the ordinary meaning (OM) of a word or phrase in a statute more objective, replicable, and transparent. However, significant questions remain as to how corpora may best be employed in the process of determining OM. In this paper, we argue that objectivity, replicability, and transparency are bolstered when legal practitioners take a hypothesis testing approach to determining ordinary meaning. In this approach, the corpus (a large collection of authentic texts) is treated as a sample of data which the practitioner may use to draw inductive inferences about the meaning of the term in question for the population to which the statute applies.

This article presents a rationale for viewing OM determinations in this way and a conceptual overview of hypothesis testing as it is employed in the wider scientific community, as well as a step-by-step demonstration of hypothesis testing applied to an OM determination.