Attributives and their Modifiers

Attributives and their Modifiers
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定语及其修饰语

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发表时间:
1972
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通讯作者:
Samuel C. Wheeler
Samuel C. Wheeler
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作者:
Samuel C. Wheeler

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The following paper is a semantical preliminary to a philosophical theory of the workings of predication in English. The basic project is to get a picture of how fairly ordinary "descriptive" predication operates and whether and why such an operation is optimal from a language-teaching and language-using point of view. We intend to use the results of this paper in giving a semantical account of the phenomenon of vagueness in English and how it can be made coherent with the view that English is a first-order language at some level of analysis. The first step in such a project, which this paper attempts, is to uncover the forms of sentences in which vague words occur. That attributive adjectives are unusual has long been recognized and ignored. Philosophers from Aristotle on have said things like, "'Tall' implicitly carries reference to a reference-class", without working out in detail what they have in mind or how it fits into a theory of language. That this glancing treatment is a strategic mistake is indicated by the following implicit claims the paper makes in the process of getting a general semantical theory of attributive adjectives: 1) The class of attributives has been taken to include words which, since they create intensional contexts, must be semantically very different in form from standard attributives. Thus, for instance, the special semantical problems of "good", which formally rule out many theories of ethics and value, have been ignored. A surprising example of such an oversight occurs in Donald Davidson's [4]. 2) The so-called "property-words", like "red", which have been universally treated as one-place predicates, are shown by a detailed theory of attributives to have the same logical form as paradigm attributives such as "tall". If "tall" is a two-place predicate, so must words like "red" be. This should give pause to people who think that words like "red" are learned by abstraction of instantiated properties.