Year: 2025
Type: book-chapter
Abstract: Although it is generally considered that even triggers both additive and scalar inferences, there are cases where only one of them can be detected. We argue that the two EVENs in Mandarin Chinese ( shenzhi and lian . dou ) may provide a clue to this puzzle. Specifically, we show that the clausal EVEN ( shenzhi ) always gives rise to a scalar inference, and its additive inference is canceled when the alternatives are mutually incompatible. Meanwhile, the phrasal EVEN ( lian . dou ) displays an almost opposite pattern, where the additive inference is always triggered, while the scalar one is sometimes less obvious. We also observe that the scalar inferences triggered by the two EVENs in Mandarin Chinese can involve different scales. The clausal shenzhi always calls for a scale that is based on a contextually supplied gradable property (Greenberg 2018 ). We propose that the clausal shenzhi in Mandarin Chinese is a speaker-oriented element, so that the scalar relation is always based on the speaker’s evaluation of how different accessible possible worlds are compared with each other within a contextually supplied scale. On the other hand, we argue that the phrasal EVEN lian . dou has an inherent additive meaning, and it obtains the scalar meaning by being associated with an Emphatic Assertion operator (Krifka 1995a ). Specifically, lian ‘include’ introduces an object to be included in the initial domain associated with the distributive/universal particle dou , and the Emphatic Assertion operator triggers an inference that the newly included object is most unlikely to be included in the domain. This creates a domain-widening effect that gives rise to the scalar inference. Finally, we support our proposal by examining crosslinguistic patterns of scalar additive particles.
Authors: Wei-wen Roger Liao, Wei-Cherng Sam Jheng
Language: English
Subfield: Language and Linguistics
Field: Arts and Humanities
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,090
OpenAlex ID: W4407169948