This thesis investigates the gradient behaviour of monadic intransitive verb classes in Turkish, under an aspectual classification of the unaccusative/unergative verb types, namely The Split Intransitivity Hierarchy. This Hierarchy claims that intransitive verb types are subject to gradient acceptability in certain syntactic constructions. The methods used in judgment elicitation studies in psychophysics, such as the magnitude estimation technique have recently been adapted to be used in capturing gradient linguistic data. Also, the practical benefits of the Internet directed researchers to design and conduct web-based experiments for linguistic data elicitation. Research on Human Computer Interaction offers suggestions for the design of more usable user interfaces. Considering these developments, in this thesis, a web based experiment interface has been designed as an extension to the magnitude estimation technique to elicit acceptability judgments on two syntactic constructions, i.e. the -mIS participle (the unaccusative diagnostic) and impersonal passivization (the unergative diagnostic) for different verb types on the Split Intransitivity Hierarchy. The experiment was conducted on the Internet.
The results show that in the two diagnostics, the verb types receive categorical or indeterminate acceptability judgments, which allows us to specify the core or peripheral status of the verbs. Within the classes we have examined, change of state verbs constitute the core unaccusative verbs, and controlled (motional and non-motional) process verbs constitute the core unergative verbs. Stative verbs and uncontrolled process verbs are peripheral unaccusatives and unergatives, respectively. Change of location verbs (with an animate subject) are close to the unergative end.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12605912/index.pdf |
| Date | 01 January 2005 |
| Creators | Cengiz, Acarturk |
| Contributors | Zeyrek, Deniz |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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