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In this article we discuss methods for investigating grammatical processing in bilinguals. We will present a methodological approach that relies on: (i) linguistic theory (in our case, morphology) for the construction of experimental materials; (ii) a design that allows for direct (within-experiment, within-participant, and within-item) comparisons of the critical conditions; and (iii) data analysis techniques that make both linear and non-linear gradient effects visible. We review recent studies of masked morphological priming in bilinguals in which the application of these methodological principles revealed highly selective interactions of age of acquisition (and the native/non-native contrast) with the linguistic distinction between inflection and derivation. We believe that such considerations are not only relevant for grammatical processing experiments, but also for studying bilingualism, and its potential cognitive advantages, more generally.
The Gradient Symbolic Computation (GSC) model presented in the keynote article (Goldrick, Putnam & Schwarz) constitutes a significant theoretical development, not only as a model of bilingual code-mixing, but also as a general framework that brings together symbolic grammars and graded representations. The authors are to be commended for successfully integrating a theory of grammatical knowledge with the voluminous research on lexical co-activation in bilinguals. It is, however, unfortunate that a certain conception of bilingualism was inherited from this latter research tradition, one in which the contrast between native and non-native language takes a back seat.
Two opposing viewpoints have been advanced to account for morphological productivity, one according to which some knowledge is couched in the form of operations over variables, and another in which morphological generalization is primarily determined by similarity. We investigated this controversy by examining the generalization of Portuguese verb stems, which fall into one of three conjugation classes. In Study 1, an elicited production task revealed that the generalization of 2nd and 3rd conjugation stems is influenced by the degree of phonological similarity between novel roots and existing verbs, whereas the 1st conjugation generalizes beyond similarity. In Study 2, we directly contrasted two distinct computational implementations of conjugation class assignment in how well they matched the human data: a similarity-driven model that captures phonological similarities, and a dual-mechanism model that implements an explicit distinction between context-free and similarity-based generalizations. The similarity-driven model consistently underestimated 1st conjugation responses and overestimated proportions of 2nd and 3rd conjugation responses, especially for novel verbs that are highly similar to existing verbs of those classes. In contrast, the expected proportions produced by the dual-mechanism model were statistically indistinguishable from human responses. We conclude that both context-free and context-sensitive processes determine the generalization of conjugations in Portuguese, and that similarity-based algorithms of morphological acquisition are insufficient to exhibit default-like generalization. (C) 2014 Elsevier Inc. All rights reserved.