Hypothesis Testing Ordinary Meaning

Abstract

The past decade has seen rapidly growing interest in the use of language corpora (large collections of machine readable texts) for the purpose of determining the ordinary or plain meaning of terms in the areas of statutory and constitutional interpretation. The primary benefits of this practice is that corpora provide reliable, replicable insights into how terms are used by language users in their ordinary, day-to-day contexts. The practice is not uncontroversial, however, as some critics have expressed concerns over the reliability of corpus linguistic analyses. In the current paper, we address these concerns by advocating for a hypothesis testing approach to corpus-linguistic analyses of ordinary meaning. First, we describe the scientific process of hypothesis testing. Then we argue that the components of an ordinary meaning determination (an inductive inference about a characteristic of a population based on that characteristic of a sample) mirror those of the classic hypothesis testing paradigm. Finally, we lead readers through an demonstration of the hypothesis testing approach to corpus-linguistic analyses of ordinary meaning in the context of H. L. A. Hart s no vehicles in the park hypothetical.