We investigated whether individuals with Williams Syndrome (WS) produce language with a bias towards statistical properties of word combinations rather than grammatical rules, resulting in an overuse of holistically stored, familiar phrases. We analysed continuous speech samples from English children with WS (n = 12), typically developing (TD) controls matched on chronological age (n = 15) and TD controls matched on language age (n = 14). Alongside word count, utterance length, grammatical complexity, and morphosyntactic errors, we measured familiarity of expressions by computing collocation strength of each word combination. The WS group produced stronger collocations than both control groups. Moreover, the WS group produced fewer complex sentences, shorter utterances, and more frequent function words than chronological-age matched controls. Language in WS may appear more typical than it is because familiar, holistically processed expressions mask grammatical and other difficulties.

This paper examines patterns in an Estonian–English bilingual child’s spontaneous speech, employing a computational application of the traceback method, which is used in usage-based linguistics. Forty-five hours of data were analyzed to check what proportion of patterns from code-mixed utterances are attested in the child’s monolingual data and in her input. Pattern overlap between the child’s and the caregivers’ speech was also examined. Results show that about one-third of code-mixed utterances can be traced back to the child’s input and one-third also to her own monolingual data. A little over half of the child’s utterances are either chunks or frame-and-slot patterns from the caregivers’ speech. These results make it evident that the traceback method can also be applied to language pairs that are genealogically more distant, though limitations exist.

Recent years have seen an increased interest in the study of heritage language bilinguals. However, much of the research on heritage bilingualism is fraught with deficit framing. In this article, we demonstrate how many of the assumptions that underlie this growing field of research and the way that heritage speakers are positioned as research subjects reveal ideologies that center and value monolingualism and whiteness. We problematize a number of ways in which these ideologies commonly show up in the frameworks and methodologies used in psycholinguistics to study this population. We advocate for frameworks such as usage-based linguistics and multicompetence that center the multidimensional experiences of bilinguals and embrace nuance and complexity. We call on the research community to examine their research designs and theories to dismantle the systems that maintain heritage bilingualism at the margins of bilingualism research.

This paper presents the first sociophonetic study of Sanapaná (Enlhet-Enenlhet), spoken by around one thousand people in Paraguay. It examines the effects of L2 (Spanish/Guaraní) fluency and loss of L1 exposure on vowel quality and within-category variability of /e, o/ productions in the Sanapaná /e, a, o/ system. Data from eleven native Sanapaná speakers suggest that age and multilingualism may have little explanatory power by themselves. Speakers living in a majority-L2 environment show greater within-category variability and increased convergence of /e, o/ toward the L2 high vowels /i, u/ than daily users of Sanapaná. This suggests that decreased L1 exposure is the main factor driving language shift-related change in Sanapaná. I explain these findings in an exemplar-theoretic framework. Although the number of speakers sampled is limited, these data provide a valuable addition to our knowledge of sociolinguistic variation in small, underrepresented communities.

Scalar inferences occur when a weaker statement like It’s warm is used when a stronger one like It’s hot could have been used instead, resulting in the inference that whoever produced the weaker statement believes that the stronger statement does not hold. The rate at which this inference is drawn varies across scalar words, a result termed ‘scalar diversity’. Here, we study scalar diversity in adjectival scalar words from a usage-based perspective. We introduce novel operationalisations of several previously observed predictors of scalar diversity using computational tools based on usage data, allowing us to move away from existing judgment-based methods. In addition, we show in two experiments that, above and beyond these previously observed predictors, scalar diversity is predicted in part by the relevance of the scalar inference at hand. We introduce a corpus-based measure of relevance based on the idea that scalar inferences that are more relevant are more likely to occur in scalar constructions that draw an explicit contrast between scalar words (e.g., It’s warm but not hot). We conclude that usage has an important role to play in the establishment of common ground, a requirement for pragmatic inferencing.