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Frequency of Classifier Constructions in American Sign Language

Williford, Lauren Lenore (2008) Frequency of Classifier Constructions in American Sign Language. Master's Thesis, University of Pittsburgh. (Unpublished)

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Abstract

Classifiers in spoken languages are generally viewed as overt morphemes within a noun phrase that serve to classify referents according to real or imputed characteristics. A 'classifier language' is so designated because it has classifier constructions, which are believed to comprise a morphosyntactic subsystem in these languages. Controversy surrounds many aspects of classifiers in spoken language. Classifiers in signed languages are, perhaps, even more controversial. Classifiers in signed languages have been categorized in a variety of ways, and some researchers debate the term, as well as their very existence. Although the terminology has been questioned, it is believed that classifiers are frequent in all signed languages, including American Sign Language. Corpora have been implemented in a variety of useful ways in spoken languages, while corpus studies in signed languages are a relatively fledgling endeavor. This study used a corpus of narratives in American Sign Language from the National Center for Sign Language and Gesture Resources (NCSLGR) to determine how frequent classifier constructions are in narrative discourse, compared to other items. Every item in the corpus was counted. Counts were taken within several individual categories, in order to compare the percentage of classifier constructions, as well as classifier types. Classifier constructions were found to comprise 7.68% of total items in the corpus. The four most frequently occurring types of classifier in the corpus are: semantic classifiers, instrument classifiers, body classifiers, and descriptive classifiers. A variety of issues may affect the percentage of classifier constructions, as well as the classifier types used, including participants, sample size, and the type of discourse involved. It is hoped that that frequency information of this kind will lead to better description, and improved typology of classifiers in signed languages.


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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Williford, Lauren Lenorelaurenlenore@gmail.com
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairMauk, Claude Ecemauk@pitt.eduCEMAUK
Committee MemberMasullo, Pascual Jose
Committee MemberKiesling, Scott F
Date: 26 September 2008
Date Type: Completion
Defense Date: 8 May 2008
Approval Date: 26 September 2008
Submission Date: 7 August 2008
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Linguistics
Degree: MA - Master of Arts
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: ASL; classifier; classifier construction; corpus; frequency; narrative; sign language
Other ID: http://etd.library.pitt.edu/ETD/available/etd-08072008-183530/, etd-08072008-183530
Date Deposited: 10 Nov 2011 19:58
Last Modified: 15 Nov 2016 13:48
URI: http://d-scholarship.pitt.edu/id/eprint/8972

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