Scales or features in verb meaning?
Verb classes as predictors of syntactic behavior
Several syntactic properties of verbal heads are accounted for through their
semantic properties. Verbal features such as agentivity, volitionality,
stativity etc. have been proven a useful tool for predicting several aspects of
their syntactic behavior such as passivization, auxiliary selection etc. In the
context of the empirical turn in current linguistics, the assumption of discrete
features is questioned by studies based on corpora or speakers’ intuitions
showing that the diagnostics of semantic features involve gradience. These
findings are challenging for grammatical theory: are we justified to assume the
existence of discrete verb classes or do the established properties indicate
scalar dimensions of meaning? Based on two empirical studies – an
acceptability study and a corpus study – the present article examines the
role of agentivity in distinguishing verb classes and in
predicting the syntactic behavior of verbs in German. Acceptability data show
that the diagnostics of agentivity involve gradience, which cannot be reduced to
random sources of variation. However, a comparison of scalar vs. categorical
models of agentivity based on these diagnostics reveals that the syntactic
variation in word order found in written corpus data is best accounted for
through a model that assumes a binary division into a ±agentive and a
non-agentive verb class.
Article outline
- 1.Introduction
- 2.Agentivity
- 3.Diagnostics of agentivity
- 3.1Method
- 3.2Results
- 3.3Discussion
- 4.Predicting voice and order
- 4.1Method
- 4.2Influence of agentivity on voice
- 4.3Influence of agentivity on order
- 4.4Discussion
- 5.Conclusion
- Notes
-
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Cited by
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Fritz-Huechante, Paola, Elisabeth Verhoeven & Julian A. Rott
2020.
Agentivity and non-culminating causation in the psych domain: Cross-linguistic evidence from Spanish and Korean.
Glossa: a journal of general linguistics 5:1
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