Property Concepts in Wolof

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Property concepts (PCs) are a class of stative notions relating to speed, age, dimension, color, value, etc. PCs are consistently lexicalized as adjectives in languages which have this category. However, PCs may also be lexicalized as nouns or roots, particularly in languages which lack a robust class of adjectives. In an array of typologically diverse and genetically unrelated languages, non-adjectival PC lexemes are found to systematically surface with possessive morphosyntax. It has recently been suggested that lexical category assignment thus reflects variation in the semantics of PC lexemes.

The Niger-Congo language Wolof splits its PC terms between nouns and adjectival verbs and exemplifies both possessive predication and direct predication strategies. Under the direction of Dr. Christopher Kennedy, Ms. Rebekah Baglini conducted primary fieldwork in Senegal to investigate the two PC constructions in the language and how they pattern together or diverge semantically. Several aspects of PC expression in Wolof are given special focus. Of particular interest is the interpretation of scalar properties associated with the two types of PC expressions, and whether they behave similarly with respect to degree modifiers, measure phrases, comparative constructions, and the formation of degree achievements. Baglini will also investigate whether particular semantic subclasses of PCs are predictably assigned to one lexical category or another and evaluate whether the Wolof facts are consistent with generalizations made in the typological literature on PCs.

The project employs a mix of field methodologies, including elicitation, production and comprehension tasks, and the collection of spontaneous speech. The findings on Wolof are be linked to longstanding questions in the theoretical literature about the nature of properties and their representation in the model theory. Moreover, this project contributes to the growing need for evaluating semantic theories against data from under-represented languages. This award also contributes to the training of a promising graduate student.
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