Minority genders in quantitative survey research: a data-driven approach to clear, inclusive, and accurate gender questions

Abstract

Abstract Whilst linguistic research on speakers of minority genders has increased in the past decade, much less is known about how they can best be included in broader (socio)linguistic research. The current paper compares the way a range of five different gender measures for survey research are filled out and evaluated by a sample of LGBTQ+ people (N = 682). It finds that providing a larger range of answering options allows researchers to gain a better view of the gender diversity in their sample, whilst preventing refusals and loss of participants. The gender question that was least likely to be refused and was rated the most accurate, most inclusive, and clearest was a six-option multiple-choice question which included a “prefer not to say” and a write-in option. This question reconciles two competing interests in the treatment of queer data: it explicitly recognizes and names minority genders and simultaneously carves out space for participants to refuse categorization or write out gender identities beyond those preset by the researcher.