![]() ![]() ![]() ![]() There are a number of issues to unpack here. The authors provide a model that can take strings of discrete elements and execute a number of primitive operations. The “assumed primitive functions” make regular reference to linearity: things like “list,” “first character,” “middle of Y,” and “string comparison.” For instance, they discuss what they term “pair” and “first” operations, which they claim “are similar in spirit to ‘Merge’ in minimalist linguistics, except they come with none of the associated machinery that is required in those theories here, they only concatenate.” Rather, it is simply what Otto Jespersen presciently termed “a notion of structure.” It is the capacity to build a structure that is thought to be innate, in addition to the arguably more mysterious content of what makes up individual words. Generative linguists, being careful with their words, are wont to stress that what is hypothesized to be innate with respect to child language acquisition is not “the structures that occur in natural language,” as Yang and Piantadosi claim. In a new study to be published in next week’s issue of PNAS, Yuan Yang and Steven Piantadosi’s paper, “One model for the learning of language,” attempts to show that language acquisition is possible without recourse to “innate knowledge of the structures that occur in natural language.” The authors claim that a domain-general, rule-learning algorithm can “acquire key pieces of natural language.” The paper provides a number of simple and elegant arguments, but ones which may not be as revolutionary as the authors seem to have intended. ![]()
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