The analogical modeling of linguistic categories

Abstract

abstractIn recent years proponents of usage-based linguistics have singled out ‘categorization’ as possibly the fundamental cognitive operation underlying the acquisition and use of language. Despite this increasing appeal to the importance of categorization, few researchers have yet offered explicit interpretations of how linguistic categories might be represented in the brain other than vague allusions to prototype theory, especially as implemented in connectionist-like frameworks. In this paper, I discuss in some detail the implications of superimposing the theoretical representations of linguistic structures onto domain-general models of categorization. I first review the evidence that instance-based, or exemplar-based, models of categorization provide empirically and theoretically better models of both domain-general categorization and of linguistic categorization than do the most commonly cited alternative models. I then argue that of the three exemplar-based models currently being applied to linguistic data, Skousen’s Analogical Model (AM) appears to provide the simplest, most straightforward account of the data and that it appears to be fully compatible with our current understanding of the psychological capabilities and operations that underlie categorization behavior.