Skip to main content
eScholarship
Open Access Publications from the University of California

UC Davis

UC Davis Electronic Theses and Dissertations bannerUC Davis

Spanish heritage speaker comprehension and production of the obligatory subjunctive

Abstract

The primary goal of this dissertation is to contribute to a predictive model of Spanish heritage grammars by applying recent advancements in machine learning to ferret out factors and covariates that give rise to the Spanish subjunctive. Given that “[p]redictive models would entail that we have a far better understanding of the various factors that shape heritage grammars” (Lohndal, 2020, p. 31), this dissertation examines how Spanish heritage speakers’ bilingual biographies affect the expression of subjunctive mood morphology in “obligatory,” or lexicosemantically “triggered” volitional, dubative, and comment clause contexts.

Using inferential lasso, a series of analyses are performed on data from 95 Central to Southern Californian Spanish heritage speakers (HSs) who took lexicality, grammaticality, and mood production tests. These HSs recognize subjunctive mood morphology, understand grammatical uses of verb mood, and produce the subjunctive 63% of the time on average, yet differences between heritage speakers with respect to proficiency levels are attested. These data demonstrate that felicitous production of the subjunctive is inferentially linked to age and order of acquisition, the Spanish of abuelas (grandmothers), a sense of authenticity when speaking Spanish, cultural affiliations, language use by friends, for religious purposes, in social media, and in self-talk and dreaming.

Multilevel modeling and a Twitter corpus are used the explore how Spanish HSs differ from Spanish native speakers (NSs), and how Spanish NS populations differ from each other for the tested constructions. This modeling demonstrates that NSs deliberately make non-normative mood choices, and that HSs and NSs are similarly sensitive to the tested predicate types and to the effects of lexical frequency.

This dissertation contributes to the field of HS grammatical research and the model of bilingualism it seeks to achieve by productively using machine learning to identify and detail the effects of bilingual background factors on the production of the subjunctive. It also provides new insights into Spanish native speakers’ non-normative verb mood choices, exactly how and where they differ from HSs, and how and where NS populations differ with respect to the use of the subjunctive for the contexts tested in this study. Finally, this dissertation provides evidence that bilingualism itself and the use of English among HSs can dramatically change grammatical outcomes.

Main Content
For improved accessibility of PDF content, download the file to your device.
Current View