Multifaceted Gender Identity Measurement As An Alternative to Forced-Choice Assessments
Abstract Number:
3371
Submission Type:
Contributed Abstract
Contributed Abstract Type:
Speed
Participants:
Thomas Belin (1), Hilary Aralis (1), Zichen Liu (1), Andrew Chuang (1), Sung-Jae Lee (1), Donatello Telesca (1)
Institutions:
(1) University of California, Los Angeles, Los Angeles, California, USA
Co-Author(s):
First Author:
Presenting Author:
Abstract Text:
While suggesting specific question wording for surveys collecting data on gender identity and sexual orientation, a 2022 National Academies of Sciences, Engineering, and Medicine report on "Measuring Sex, Gender Identity, and Sexual Orientation" recognized limitations of "forced-choice measurement" using multiple-choice items and recommended further research into representing nonbinary gender identity and gender fluidity. Here we describe a framework for "Multifaceted Gender Identity Measurement" (M-GIM) asking respondents about the extent to which they agree or disagree with a series of gender-identity and sexual-orientation prompts, anticipating that identifiable clusters will emerge from patterns in ordinal responses without requiring individuals to self-classify into one of a limited number of categories. After highlighting the appeal of keeping such queries free of the implicit constraints and negative associations built into mutually-exclusive response options, the presentation will discuss a conceptual framework for investigating disparities in quality-of-life outcomes across population subgroups characterized by similar gender-identity or sexual-orientation profiles.
Keywords:
gender identity|sexual orientation|ordinal data|cluster analysis|nonbinary|gender fluidity
Sponsors:
Social Statistics Section
Tracks:
Statistical Measurement of Social Issues and Trends
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