Literaturnachweis - Detailanzeige
| Autor/inn/en | Howitt, Katherine; Dey, Soumik; Sakas, William Gregory |
|---|---|
| Titel | Gradual Syntactic Triggering: The Gradient Parameter Hypothesis |
| Quelle | In: Language Acquisition: A Journal of Developmental Linguistics, 28 (2021) 1, S.65-96 (32 Seiten)Infoseite zur Zeitschrift
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| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| ISSN | 1048-9223 |
| DOI | 10.1080/10489223.2020.1803329 |
| Schlagwörter | Linguistic Theory; Language Acquisition; Computational Linguistics; Guidelines; Linguistic Input; Grammar; Language Universals; Ambiguity (Semantics); Syntax; Form Classes (Languages); Learning Processes |
| Abstract | In this article, we propose a reconceptualization of the principles and parameters (P&P) framework. We argue that in lieu of discrete parameter values, a parameter value exists on a gradient plane that encodes a learner's confidence that a particular parametric structure licenses the utterances in the learner's linguistic input. Crucially, this gradient parameter hypothesis obviates the need for default parameter values. Default parameter values can be put to use effectively from the perspective of linguistic learnability but are lacking in terms of empirical and theoretical consistency. We present findings from a computational implementation of a gradient P&P learner. The findings suggest that the gradient parameter hypothesis provides the basis for a viable alternative to existing computational models of language acquisition in the classic P&P paradigm. We close with a brief discussion of how a gradient parameter space offers a path to address shortcomings that have been attributed to the P&P framework. (As Provided). |
| Anmerkungen | Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2024/1/01 |
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