Domain-specific in the context of "Cognitive development"

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⭐ Core Definition: Domain-specific

Domain specificity is a theoretical position in cognitive science (especially modern cognitive development) that argues that many aspects of cognition are supported by specialized, presumably evolutionarily specified, learning devices. The position is a close relative of modularity of mind, but is considered more general in that it does not necessarily entail all the assumptions of Fodorian modularity (e.g., informational encapsulation). Instead, it is properly described as a variant of psychological nativism. Other cognitive scientists also hold the mind to be modular, without the modules necessarily possessing the characteristics of Fodorian modularity.

Domain specificity emerged in the aftermath of the cognitive revolution as a theoretical alternative to empiricist theories that believed all learning can be driven by the operation of a few such general learning devices. Prominent examples of such domain-general views include Jean Piaget's theory of cognitive development, and the views of many modern connectionists. Proponents of domain specificity argue that domain-general learning mechanisms are unable to overcome the epistemological problems facing learners in many domains, especially language. In addition, domain-specific accounts draw support from the surprising competencies of infants, who are able to reason about things like numerosity, goal-directed behavior, and the physical properties of objects all in the first months of life. Domain-specific theorists argue that these competencies are too sophisticated to have been learned via a domain-general process like associative learning, especially over such a short time and in the face of the infant's perceptual, attentional, and motor deficits. Current proponents of domain specificity argue that evolution equipped humans (and indeed most other species) with specific adaptations designed to overcome persistent problems in the environment. For humans, popular candidates include reasoning about objects, other intentional agents, language, and number. Researchers in this field seek evidence for domain specificity in a variety of ways. Some look for unique cognitive signatures thought to characterize a domain (e.g. differences in ways infants reason about inanimate versus animate entities). Others try to show selective impairment or competence within but not across domains (e.g. the increased ease of solving the Wason Selection Task when the content is social in nature). Still, others use learnability arguments to argue that a cognitive process or specific cognitive content could not be learned, as in Noam Chomsky's poverty of the stimulus argument for language.

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Domain-specific in the context of Generative grammar

Generative grammar is a research tradition in linguistics that aims to explain the cognitive basis of language by formulating and testing explicit models of humans' subconscious grammatical knowledge. Generative linguists tend to share certain working assumptions such as the competenceperformance distinction and the notion that some domain-specific aspects of grammar are partly innate in humans. These assumptions are often rejected in non-generative approaches such as usage-based models of language. Generative linguistics includes work in core areas such as syntax, semantics, phonology, psycholinguistics, and language acquisition, with additional extensions to topics including biolinguistics and music cognition.

Generative grammar began in the late 1950s with the work of Noam Chomsky, having roots in earlier approaches such as structural linguistics. The earliest version of Chomsky's model was called Transformational grammar, with subsequent iterations known as Government and binding theory and the Minimalist program. Other present-day generative models include Optimality theory, Categorial grammar, and Tree-adjoining grammar.

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