My primary research program investigates the interconnectedness of social ideologies, language variation, and cognition. In my work, I have argued for a dual-pathway by which social information is integrated into lexical production and processing. By one route, language and social experiences show up in measures like frequency (e.g. left-wing Americans may be more frequently exposed to gender-neutral language such as “congressperson” than their right-wing counterparts). By the other, language users bring their overt societally held-beliefs to bear on language production and processing above and beyond the level of frequency and language experience.

In examining this line of inquiry, I have focused specifically on issues of gender and (American) political identity. Papineau et al. (2022) presents evidence from gender-neutral language such as “congressperson” that, while processing time of such terms is not modulated by political identity, production rates are, with left-wing and gender-progressive individuals selecting gender-neutral language more often than their more (gender-)conservative counterparts. I similarly show in Papineau & Degen (2024) that it is possible to model this kind of variation using a socially-enriched implementation of the Rational Speech Act framework, demonstrating how language users’ beliefs about their interlocutors allow queer and alt-right web authors to play with referring expression variation when discussing transgender women.

My dissertation (chairs: Robert Hawkins, Robert Podesva) deals with this dual-route proposal, and I am currently deploying an experiment designed to tease apart how social identity and alignment modulates frequency effects in novel word learning.