Tips from xxboy:
Researchers, take note.
It is incredibly disappointing (not to mention invalidating and possibly dysphoria-inducing) for a trans* or intersex person to voluntarily begin a survey being advertised to the LGBT or LGBTQI+ community only to have their identity/identities not represented. And this happens ALL the time.
Fortunately, there are actually really easy ways that people constructing and promoting these surveys can avoid this! And if you don’t do LGBTQI+-specific research, most of these rules, specifically those tackling demographic questionnaires, will still be relevant to you!
- Use the term “sex assigned at birth” instead of sex. Asking someone their sex, even with “biological” as a qualifier, is pretty loaded and unclear for someone whose biological sex characteristics have changed (due to hormone replacement therapy, for example) or for intersex individuals whose biological traits don’t fall into our limited sex categories. Asking for sex assigned at birth is a way to be affirming of people’s gender and sex identities while still gathering the data we use to categorize people (which is worth of a post of its own). (If your study only includes people from the US, your options can be male or female only, as these are the only sexes legally allowed on birth certificates -if your study is international, however, you will need to include at least a third option.)
- Include gender as a separate question. Not only is this going to be affirming because it acknowledges that it is possible and not abnormal to have a gender that is different from your sex assigned at birth, it’s going to give you better data. Studies often say “males were more likely to blah blah than females,” and I always wonder if that finding holds for people who were assigned male at birth vs. people who were assigned female at birth or if the finding actually represents differences between people living as men and people living as women. And of course, that leads to a question of where people who do not identify as men or women fit or intersex individuals whose assigned sex means nada about their biological traits. (Again, that will be another post.)
- State how you are defining gender and sex (assigned at birth if you follow rule #1). Be clear. And when you are defining these, use language that is inclusive and validating. I think a good way to set this up is something like the following: “Gender identity is a person’s internal sense of being a woman, a man, both, or neither. This often corresponds with their public role (e.g., living as a woman), and may or may not match their sex assigned at birth, which is the sex label given to an infant and listed on their birth certificate.” It can be helpful to provide examples, but if you decide to do this always provide inclusive examples, so: “If you are a transgender woman, you may have a gender identity of female and a sex assigned at birth of male. If you are a non-transgender woman, you may have a gender identity of female and a sex assigned at birth of female.”
- Give people options beyond male and female. There should never be a drop down menu for gender that only includes two categories. Never ever. It’s inaccurate, will result in misrepresenting your sample (read: is BAD SCIENCE), will be invalidating to a whole host of individuals, and will likely cause trans* people to stop participating in your study and probably turn them off future research studies – which is a major loss for the whole research community! A good way to be inclusive is to allow for a write-in for gender/gender identity. You can either code these into predetermined categories (not just two, though!) or you can also ask participants to select a listed identity that is closest to their own. I have included non-binary as my third option – I think it is more normalizing than “other.”
- Make sure you actually want to study trans* and/or intersex people! (Note that these are not necessarily mutually exclusive categories but also not necessarily mutually inclusive, either.) If you are studying sexual minority-related issues, chances are that the T and/or I that you’re including in your acronym (e.g., “LGBT study”) is out of place. You should still make sure your demographics questions are inclusive because trans* and intersex people can belong to sexual minority groups, too, but don’t include trans* or intersex in your titling or advertising of the study if you aren’t specifically studying issues of trans* people or intersex, mmkay?
- If you are only studying binary-identified participants, say so! I get it, y’all. I do research. We need categories. Is this a downside to quantitative research? Absolutely. But it’s somewhat of a reality, especially if you want to get published. Sexuality research is tough because so much of it rests on labels that depend on binary gender categories. For example, “same-sex,” which usually means same-gender, is tricky when you have someone who is non-binary-identified. But rather than just not including options that reflect these sexualities or identities, state in your inclusion criteria that you are interested in people with binary gender identities. Nothing is more invalidating than having your identity unacknowledged as an option.
If anyone reading this thinks I’m leaving something off, please reply/repost or message me and I’ll update it. I’m thinking this will be a living document kind of blog post.