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Lillian Rivera on Thinking beyond the gender binary on assessments: Notes from the field

I am Lillian Rivera, After School Program Director for Hetrick-Martin Institute, a community-based organization that provides programs for LGBT teens that focus on arts and culture, health and wellness, job readiness, academic enrichment as well as counseling and HIV prevention services to 1,500 youth annually.  HMI’s HIV prevention work allows us to work with various evaluators using different quantitative and qualitative assessments.

I’m writing to share a field perspective on the issue of adding LGBTQ questions to these assessments.  The AEA365 post from John Daws in February notes “’Are you Male or Female?’ That simple question might be adequate sometimes, but a good evaluator should realize when it isn’t.”  Evaluating programs that serve HMI’s population certainly demands that the question of gender be approached with thinking beyond the traditional binary of male and female, but often instruments don’t allow that.

Even instruments  with choices for male, female, and transgendered, which seem inclusive and accurate, allowing survey takers to “see themselves in the data” and the evaluation team to learn about the population served, can limit the accuracy of reflected demographics.

Lesson Learned: Since LGBTQ populations, particularly youth, may be at various states in their gender identity transition at different survey time points respondents frequently connect to different gender labels at different times and therefore may select different answers for each.  This can yield inaccurate information and limit the ability to interpret findings.

Lesson Learned: A great solution is to use a secondary measure on which program or site staff confidentially indicate which participants are gender variant, individuals whose gender identity may vary.  Triangulating staff interview data, clinical intake statistics on participants, and initial demographics findings from the participant survey let the evaluation team identify the survey’s inaccuracy.  Meeting with program staff yielded the use of the secondary measure to give accurate data while respecting participant process and confidentiality issues.

Bonus: Having staff help generate the solution created buy-in to the use of the measure and the evaluation process overall.

Hot Tip: When instrument and observational reflections seem at odds, work with practitioners to find innovative measurement solutions.  Don’t be afraid to think outside of the box—or the gender binary!

Do you have questions, concerns, kudos, or content to extend this aea365 contribution? Please add them in the comments section for this post on the aea365 webpage so that we may enrich our community of practice. Would you like to submit an aea365 Tip? Please send a note of interest to aea365 is sponsored by the American Evaluation Association and provides a Tip-a-Day by and for evaluators.

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  • Sara · July 26, 2011 at 10:52 am

    Thank you for your comment, Vidhya – I was thinking something similar. Sometimes we might learn the most by seeing how people identify themselves. This was the case for me in evaluating health services for transgender clients.

    We left room for clients to self-identify, and found that it was greatly variant. It also taught us that many people who were further along in their transition (post-surgery) found even the term “transgender” to be inappropriate and sometimes inconsiderate. For some of these clients, they wanted to be referred to as their preferred gender alone, without the “trans” label. It was a very interesting lesson in how we could be more sensitive!


  • Vidhya Shanker · July 9, 2011 at 11:14 am

    Thank you! But some of this seems specific to a social work/ clinical context. In organizations where program participants are not necessarily just receiving services, but in leadership positions and organizing campaigns, etc., do you see any value in allowing program participants themselves choose how they identify in terms of gender, sexuality (and indeed, race/ ethnicity)? I know it’s messier for analysis, but I’m starting to think that we often limit our own understanding, and the identities of those in our evaluations, simply because our current frameworks haven’t necessarily caught up with reality.


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