We assessed whether and under what conditions noncanonical agreement patterns occur in Russian, with the goal of understanding the factors involved in normal agreement. Russian is a morphosyntactically rich language in which agreement involves features for number, gender, and case. If consistent, overt specification of number and gender agreement features supports agreement processes in language production, agreement should be less vulnerable to number and gender attraction than in languages with sparse agreement morphology. A related question was the degree to which notional number influences agreement patterns in morphologically rich languages. We varied the grammatical and notional number properties of sentence subjects and examined the effects on the predicate in sentence completion tasks using native Russian speakers. Noncanonical agreement occurred, but at rates lower than those observed in English and other languages without rich number morphology. Noncanonically plural predicates occurred more often after notionally plural subjects, suggesting notional number agreement, but the incidence was also lower than in languages with sparser agreement morphology. Gender attraction was almost nonexistent. The results suggest that morphology arbitrates grammatical agreement processes and reduces the impact of variations in notional number.
The assumption that attribute phrases like nuclear physicist constitute a bracketing paradox which may be resolved by special rules such as head rules, rebracketing rules, and productive backformation has gone unchallenged for more than a decade. This paper argues that such structural solutions do not work, since the same scope problems are reflected in phrases based on underived words with no morphological bracketing at all. In their place, a solution based on DECOMPOSlTIONAL or FEATURAL COMPOSITION is proposed, in which attributes compose semantically not with the full set of features of their head, but rather with only one particular feature. This solution reduces the wide and narrow scope readings of attribute phrases to a question of which feature is selected, in effect making all attribute composition the same and obviating the distinction between wide and narrow scope readings of attribute phrases,
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.