Scaling Up: Representing Gender Diversity in Survey Research

Abstract

Survey measures of gender have been critiqued for failing to reflect the diversity of the population. Conventionally, respondents to national surveys are categorized as female or male. Calls for improvement have centered on adding additional categories, such as transgender. We propose that in addition to revising categorical gender measures, national surveys should incorporate gradational measures of femininity and masculinity to better reflect gender diversity and sharpen models of gender inequality. Our results from two national pilot studies show that conventional measures mask significant variation within the categories of female and male. For example, less than a quarter of respondents reported that they are very feminine or masculine, respectively, and not at all the other. We also demonstrate that scale responses can be treated as independent variables in studies of inequality or as dependent variables that allow gender identification to be an outcome of social processes.