Theory-driven corpus research : using corpora to inform aspect theory.

Xiao, Richard Z. (2008) Theory-driven corpus research : using corpora to inform aspect theory. In: Corpus Linguistics: An International Handbook :. Handbooks of Linguistics and communication Science, 1 . Mouton de Gruyter, Berlin, Germany. ISBN 978-3110180435

Full text not available from this repository.

Abstract

This article maintains that linguistics is the study of language as reflected by our knowledge, as well as use, of language, contrary to Chomskyan linguists' assertion that performance data cannot be the subject of linguistics. A comparison of the three types of data used in linguistics, namely introspective data, elicited data and corpus data, shows that corpus data is more reliable than the first two types as a corpus can provide data that is attested, contextualized, and quantitative. The corpus-based approach can achieve improved reliability also because it does not go to the extreme of rejecting intuition while attaching importance to empirical data. Whilst corpora can be used to verify and revise existing linguistic theories, or to provide what intuition alone cannot discern, on the basis of which entirely new linguistic theories can be developed, the sharp distinction found in the literature between the corpus-based vs. corpus-driven approaches is overstated. This article also presents a case study of aspect which demonstrates that a marriage between theory-driven and corpus-based approaches to linguistics can lead to more accurate linguistic descriptions and hence theories.

Item Type:
Contribution in Book/Report/Proceedings
Additional Information:
The PDF manuscript is not "beautified" so as to fit the publisher's stylesheet. A PDF offprint will be provided when available.
Uncontrolled Keywords:
/dk/atira/pure/researchoutput/libraryofcongress/p1
Subjects:
?? corpuslinguistic theoryaspectp philology. linguistics ??
ID Code:
61
Deposited By:
Deposited On:
17 Jun 2005
Refereed?:
No
Published?:
Published
Last Modified:
16 Jul 2024 02:08