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Roots of modality

Aynat Rubinstein, University of Massachusetts Amherst

Abstract

This dissertation explores the interplay of grammar and context in the interpretation of modal words like ought, necessary , and need. The empirical foci of the discussion are patterns in the use of strong and weak necessity modals in conversation, and the interpretation of syntactically and semantically versatile modals like need in the various grammatical configurations they appear in across languages. ^ It is argued that a sensitivity to collective commitments in a conversation is necessary for understanding certain aspects of modal strength, in particular the traditional distinction between strong and weak necessity modals (exhibited by must and ought to in English). It is proposed that strong necessity modals can only reference priorities that are presupposed to be collectively committed to, whereas weak necessity modals are evaluated with respect to a mixed bag of priorities, crucially including ones that are presupposed not to be collectively committed to. A domain restriction approach to weak necessity is adopted, following a demonstration that it is superior to a number of probabilistic alternatives. ^ Modal verbs and adjectives that take both infinitival and nominal complements are shown to pattern alike across languages in requiring a teleological, or goal-oriented interpretation when their complements are not infinitives (but rather noun phrases or certain Complementizer Phrases). This limitation is lifted with infinitival complements, showing that transitive configurations of certain intensional verbs are not semantically equivalent to the infinitival configurations of the same verbs. ^ A result of this research is a fine grained analysis of the differences between closely related necessity modals and attitude verbs. ^

Subject Area

Linguistics

Recommended Citation

Rubinstein, Aynat, "Roots of modality" (2012). Doctoral Dissertations Available from Proquest. AAI3545982.
http://scholarworks.umass.edu/dissertations/AAI3545982

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