Abstract

Scholars and practitioners interested in legal interpretation have become increasingly interested in corpus-linguistic methodology. Lee and Mouritsen (2018) developed and helped popularize the use of concordancing and collocate displays (of mostly COCA and COHA) to operationalize a central notion in legal interpretation, the ordinary meaning of expressions. This approach provides a good first approximation but is ultimately limited. Here, we outline an approach to ordinary meaning that is intensionalist (i.e., 'feature-based'), top-down, and informed by the notion of cue validity in prototype theory. The key advantages of this approach are that (i) it avoids the which-value-on-a-dimension problem of extensionalist approaches, (ii) it provides quantifiable prototypicality values for things whose membership status in a category is in question, and (iii) it can be extended even to cases for which no textual data are yet available. We exemplify the approach with two case studies that offer the option of utilizing survey data and/or word embeddings trained on corpora by deriving cue validities from word similarities. We exemplify this latter approach with the word vehicle on the basis of (i) an embedding model trained on 840 billion words crawled from the web, but now also with the more realistic application (in terms of corpus size and time frame) of (ii) an embedding model trained on the 1950s time slice of COHA to address the question to what degree Segways, which didn't exist in the 1950s, qualify as vehicles in this intensional approach.

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