A Critical Examination of Open-Ended SOGI Responses and LGBTQ-Modules in Population-Based Surveys: Evidence from Chile

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Abstract

Recent advances in the measurement of sexual orientation and gender identity (SOGI) have encouraged the inclusion of open-ended response options in population-based surveys to increase flexibility and inclusivity. While these options allow respondents to describe identities in their own terms, they also introduce significant methodological challenges related to classification, recoding, and survey routing. This paper critically examines the implications of open-ended SOGI fields and LGBTQ-specific question modules in large-scale nationally representative surveys using Chile’s National Health, Sexuality, and Gender Survey (ENSSEX 2023).

Drawing on descriptive analyses, cross-tabulations, regression models predicting selection of open-ended responses, and close examination of survey instruments and derived variable construction, the paper analyzes three interrelated issues: who responds to open-ended SOGI items (i.e. who selects “Other”), how open-ended responses are recoded into analytic variables, and how survey filtering and routing shape respondents’ inclusion in LGBTQ-specific measures. Preliminary findings indicate that a substantial share of open-ended sexual orientation responses reflect misinterpretation rather than the articulation of non-normative identities (i.e. many respondents entering gender terms such as “man” or “woman”). Cross-referencing these responses with different measures of sexual attraction and gender identification suggests that most of these cases likely involve heterosexual, cisgender or non-queer identifying respondents, highlighting the measurement errors that open-ended identification can entail.

Beyond documenting these challenges, the paper shows how classification decisions and survey routing jointly influence which respondents are categorized as LGBTQ+ and which are exposed to LGBTQ-specific survey items. Using the ENSSEX 2023 as a case study, this analysis sheds light on how efforts to increase inclusivity in population-based data collection efforts through open-ended SOGI measures can simultaneously generate new forms of exclusion through measurement design, contributing to scholarship on survey methodology, categorization, and the production of populations.

Author

• Cristián Valenzuela-Méndez, Northwestern University