Semantic and morphophonological productivity in the Kiitharaka gender system: A quantitative study

Nominal classification systems are characterized by diverse and sometimes complex gender assignment rules that interact in dynamic ways. The specifics of how gender assignment works can vary widely from language to language. Nominal classification systems of Bantu languages in particular have been the subject of long-standing debate. Traditional accounts of gender assignment are based principally on abstract semantic features which have been found to be unreliable in at least some present-day Bantu languages. Such analyses, in addition to relying on arbitrary sets of semantic features, are problematic, since they provide no clear definition of what it means for a particular feature to be productive. Here we follow a more recent approach, using corpus data to evaluate productivity. We compiled a corpus of 2,327 Kîîtharaka nouns, each coded for a set of semantic and morphophonological features. We then used the Tolerance Principle (Yang, 2016) to measure the predicted productivity of each feature. Our results indicate that morphophonological features are highly productive in Kîîtharaka. However, of the tested semantic features, relatively few were predicted to be productive, including Human, and some evaluative features (Augmentative, Pejorative, Diminutive). The feature Human is in fact only productive for a specific subset of nouns, indicating a possible interaction between features. We discuss why this might be, and highlight the implications of this approach for Kîîtharaka, and for the study of gender assignment in Bantu more broadly.