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The language capacity: architecture and evolution

Overview of attention for article published in Psychonomic Bulletin & Review, July 2016
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Title
The language capacity: architecture and evolution
Published in
Psychonomic Bulletin & Review, July 2016
DOI 10.3758/s13423-016-1078-6
Pubmed ID
Authors

Noam Chomsky

Abstract

There is substantial evidence that the human language capacity (LC) is a species-specific biological property, essentially unique to humans, invariant among human groups, and dissociated from other cognitive systems. Each language, an instantiation of LC, consists of a generative procedure that yields a discrete infinity of hierarchically structured expressions with semantic interpretations, hence a kind of "language of thought" (LOT), along with an operation of externalization (EXT) to some sensory-motor system, typically sound. There is mounting evidence that generation of LOT observes language-independent principles of computational efficiency and is based on the simplest computational operations, and that EXT is an ancillary process not entering into the core semantic properties of LOT and is the primary locus of the apparent complexity, diversity, and mutability of language. These conclusions are not surprising, since the internal system is acquired virtually without evidence in fundamental respects, and EXT relates it to sensory-motor systems that are unrelated to it. Even such properties as the linear order of words appear to be reflexes of the sensory motor system, not available to generation of LOT. The limited evidence from the evolutionary record lends support to these conclusions, suggesting that LC emerged with Homo sapiens or not long after, and has not evolved since human groups dispersed.

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Geographical breakdown

Country Count As %
Unknown 140 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 19%
Student > Bachelor 21 15%
Researcher 16 11%
Student > Master 14 10%
Professor 10 7%
Other 26 19%
Unknown 26 19%
Readers by discipline Count As %
Linguistics 40 29%
Psychology 20 14%
Arts and Humanities 8 6%
Neuroscience 6 4%
Computer Science 5 4%
Other 30 21%
Unknown 31 22%