The ability to convey our thoughts using an infinite number of linguistic expressions is one of the hallmarks of human language. Understanding the nature of the psychological mechanisms and representations that give rise to this unique productivity is a fundamental goal for the cognitive sciences. A long-standing hypothesis is that single words and rules form the basic building blocks of linguistic productivity, with multiword sequences being treated as units only in peripheral cases such as idioms. The new millennium, however, has (...) seen a shift toward construing multiword linguistic units not as linguistic rarities, but as important building blocks for language acquisition and processing. This shift—which originated within theoretical approaches that emphasize language learning and use—has far-reaching implications for theories of language representation, processing, and acquisition. Incorporating multiword units as integral building blocks blurs the distinction between grammar and lexicon; calls for models of production and comprehension that can accommodate and give rise to the effect of multiword information on processing; and highlights the importance of such units to learning. In this special topic, we bring together cutting-edge work on multiword sequences in theoretical linguistics, first-language acquisition, psycholinguistics, computational modeling, and second-language learning to present a comprehensive overview of the prominence and importance of such units in language, their possible role in explaining differences between first- and second-language learning, and the challenges the combined findings pose for theories of language. (shrink)

The present paper argues that there is ample corpus evidence of statistical preemption for learners to make use of. In the case of argument structure constructions, a verbi is preempted from appearing in a construction A, CxA, if and only if the following probability is high: P(CxB|context that would be suitable for CxA and verbi). For example, the probability of hearing a preemptive construction, given a context that would otherwise be well-suited for the ditransitive is high for verbs like explain (...) that overwhelmingly appear in the dative, and low for verbs like tell that readily appear in the ditransitive. Strength of statistical preemption is determined both by this probability, and by the frequency (ln (F)) of a verb in a preemptive construction when the context is at least as well suited to the preempted construction. The critiques of preemption by Stefanowitsch (Cognitive Linguistics 19: 513–531, 2008, this volume) are countered by arguing that the relevant probabilities were not considered. Moreover, we find evidence that constructions are somewhat less constrained when yoked to non-alternating verbs, as Stefanowitsch (cf. this volume) suggests should be the case. (shrink)