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Coding causal–noncausal verb alternations: A form–frequency correspondence explanation
Coding causal–noncausal verb alternations: A form–frequency correspondence explanation
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Coding causal–noncausal verb alternations: A form–frequency correspondence explanation
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Coding causal–noncausal verb alternations: A form–frequency correspondence explanation
Coding causal–noncausal verb alternations: A form–frequency correspondence explanation

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Coding causal–noncausal verb alternations: A form–frequency correspondence explanation
Coding causal–noncausal verb alternations: A form–frequency correspondence explanation
Journal Article

Coding causal–noncausal verb alternations: A form–frequency correspondence explanation

2014
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Overview
We propose, and provide corpus-based support for, a usage-based explanation for cross-linguistic trends in the coding of causal–noncausal verb pairs, such as raise/rise, break (tr.)/break (intr.). While English mostly uses the same verb form both for the causal and the noncausal sense (labile coding), most languages have extra coding for the causal verb (causative coding) and/or for the noncausal verb (anticausative coding). Causative and anticausative coding is not randomly distributed (Haspelmath 1993): Some verb meanings, such as 'freeze', 'dry' and 'melt', tend to be coded as causatives, while others, such as 'break', 'open' and 'split', tend to be coded as anticausatives. We propose an explanation of these coding tendencies on the basis of the form–frequency correspondence principle, which is a general efficiency principle that is responsible for many grammatical asymmetries, ultimately grounded in predictability of frequently expressed meanings. In corpus data from seven languages, we find that verb pairs for which the noncausal member is more frequent tend to be coded as anticausatives, while verb pairs for which the causal member is more frequent tend to be coded as causatives. Our approach implies that linguists should not rely on form–meaning parallelism when trying to explain cross-linguistic or language-particular patterns in this domain.