The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
Poverty of the Stimulus Revisited
Abstract
A central goal of modern generative grammar has been to discover invariant properties of human languages that reflect “the innate schematism of mind that is applied to the data of experience” and that “might reasonably be attributed to the organism itself as its contribution to the task of the acquisition of knowledge” (Chomsky, 1971). Candidates for such invariances include the structure dependence of grammatical rules, and in particular, certain constraints on question formation. Various “poverty of stimulus” (POS) arguments suggest that these invariances reflect an innate human endowment, as opposed to common experience: Such experience warrants selection of the grammars acquired only if humans assume, a priori, that selectable grammars respect substantive constraints. Recently, several researchers have tried to rebut these POS arguments. In response, we illustrate why POS arguments remain an important source of support for appeal to a priori structure‐dependent constraints on the grammars that humans naturally acquire.
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Cites
ASPECTS OF THE THEORY OF SYNTAX
Chomsky, N. (1964) · doi:10.21236/ad0616323 · Cited by 13,587
Self-citationChomsky, N. (1957) · doi:10.1515/9783112316009 · Cited by 7,885
Self-citationMarr, D. (1982) · Cumulative Index of Computer Aided Architectural Design · Cited by 5,733
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Smith, T. L., & Chomsky, N. (1982) · The Philosophical Review · doi:10.2307/2184681 · Cited by 2,808
Self-citationChomsky, N. (1980) · Behavioral and Brain Sciences · doi:10.1017/s0140525x00001515 · Cited by 2,650
Self-citationLanguage and the mind: (400082009-004)
Chomsky, N. (1968) · PsycEXTRA Dataset · doi:10.1037/e400082009-004 · Cited by 2,504
Self-citation(1975) · Medical Entomology and Zoology · Cited by 2,045
Learning and development in neural networks: the importance of starting small
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“that chooses among different types of grammars (Perfors, Tenenbaum, & Regier, 2011); and bigram or trigram statistical methods, along with a neural network model (Reali & Christiansen, 2005; Elman, 2003).”
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Cited by
Neural Network Acceptability Judgments
Warstadt, A., Singh, A., & Bowman, S. R. (2019) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00290 · Cited by 1,215
Emergent linguistic structure in artificial neural networks trained by self-supervision
Manning, C. D., Clark, K., Hewitt, J., Khandelwal, U., & Levy, O. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1907367117 · Cited by 339
The mystery of language evolution
Hauser, M. D., Yang, C., Berwick, R. C., Tattersall, I., Ryan, M. J., Watumull, J., Chomsky, N., & Lewontin, R. C. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2014.00401 · Cited by 329
Self-citationThe role of language processing in language acquisition
Phillips, C., & Ehrenhofer, L. (2015) · Linguistic Approaches to Bilingualism · doi:10.1075/lab.5.4.01phi · Cited by 123
What Artificial Neural Networks Can Tell Us about Human Language Acquisition
Warstadt, A., & Bowman, S. R. (2022) · Algebraic Structures in Natural Language · doi:10.1201/9781003205388-2 · Cited by 111
Metadata
- Authors
- Berwick, R. C., Pietroski, P., Yankama, B., & Chomsky, N.
- Venue
- Cognitive Science
- Publisher
- Wiley
- Published
- 2011-08-08
- Volume
- 35
- Issue
- 7
- Pages
- 1207-1242
- ISSN
- 0364-0213 (ISSN-L)
- 1551-6709
- OpenAlex
- W2140324965
- Cited by
- 447
- References
- 43
- FWCI
- 340.49
- Type
- journal article
- Language
- en
- Open access
- closed
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