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Categorization and Naming in Children: Problems of Induction
Abstract
In this landmark work on early conceptual and lexical development, Ellen Markman explores the fascinating problem of how young children succeed at the task of inducing concepts. Backed by extensive experimental results, she challenges the fundamental assumptions of traditional theories of language acquisition and proposes that a set of constraints or principles of induction allows children to efficiently integrate knowledge and to induce information about new examples of familiar categories.
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Citations
Cited by
Learnability and Cognition: The Acquisition of Argument Structure
Naigles, L. (1991) · Language and Speech · doi:10.1177/002383099103400105 · Cited by 1,618
Conceptual Foundations of Evolutionary Psychology
Tooby, J., & Cosmides, L. (2015) · The Handbook of Evolutionary Psychology · doi:10.1002/9780470939376.ch1 · Cited by 658
Deriving Categories to Achieve Goals
Barsalou, L. W. (1991) · Psychology of Learning and Motivation · doi:10.1016/s0079-7421(08)60120-6 · Cited by 531
Learning New Words: Phonotactic Probability in Language Development
Storkel, H. L. (2001) · Journal of Speech, Language, and Hearing Research · doi:10.1044/1092-4388(2001/103 · Cited by 441
Pretend Play Skills and the Child's Theory of Mind
Lillard, A. S. (1993) · Child Development · doi:10.1111/j.1467-8624.1993.tb02914.x · Cited by 423
Metadata
- Authors
- Markman, E. M.
- Venue
- The MIT Press eBooks
- Publisher
- The MIT Press
- Published
- 1991
- OpenAlex
- W4246853460
- Cited by
- 444
- References
- 0
- FWCI
- 11.88
- Type
- book
- Language
- en
- Open access
- closed
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- Markman, E. M. (1991). Categorization and Naming in Children: Problems of Induction. The MIT Press eBooks. https://doi.org/10.7551/mitpress/1750.001.0001
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.