I’ve been giving my talk about gender for developers for a few years now, and it’s constantly being refined. Last year I gave the same version of the talk at Edinburgh and York universities. I noticed that researchers have different reasons for asking about gender and for them, it is not as avoidable as it is for commercial companies. I have spent way too long on r/samplesize and I’ve seen a lot of questionnaires with badly written gender questions and a general misunderstanding of gender, even in surveys that are explicitly about gender or gender-adjacent topics. This blog post is specifically for researchers and academics; it will cover why we ask about the gender (and other characteristics) of our participants; why this might cause issues for them and some best practice around asking about, and reporting on, gender.
Why do we ask for participant gender?
The main feedback I received from academics is that they can’t avoid asking about their participants’ gender. While I think it’s not impossible, it is correct that asking about gender, age, location and race are standard questions. Why is this?
The main reason to ask about these demographics is because we need to describe the sample of people who have participated in our research. This allows other researchers to spot issues that might be addressed in future research, for example participants in my project about player experience was 80% male, a future student might redo my work with a majority female population and compare the results. It also helps to show how representative our sample was. This is not the same as checking it is representative of the general population, but the population of people we care about. Going back to the example of my work, around 45% of the people who play video games are women, therefore my 20% women sample was not very representative. This means that my results may not be valid when applied to the entire game-playing population.
A secondary reason might be because we want to know how to refer to participants in our analysis. This could be as small as wanted to know pronouns where referring to quotes, or gender could be one of the central points of the analysis. This is much more dependent on the question the researcher is trying to answer, and therefore is less avoidable. However, the issues and recommendations in this blogpost will still apply.
Why could this cause issues for some people?
There are three sets of people I am going to cover in this section; transgender people, non-binary people and people who are a gender minority in a space. The main point to remember about these three populations is that they are vulnerable. This means they are worried about their safety when they are giving you information, not just about gender. Even if data is anonymised it can be easy to pick a particular person out, especially in a small population that is visible. As an example, an anonymised list of attendees of a conference was made available to organisers. My row is easy to find as I was the only non-binary speaker. A professor using their students as participants might be able to easily pull out the only 40-year-old woman in their class.
For a lot of trans people and most non-binary people, there is a difference between their legal gender and their actual gender. They may be living in different genders in different circumstances; for example, I’m out to friends but not to family. In the UK, non-binary genders are not legally recognised; my birth certificate, passport and driving licence all say I’m female. This is my assigned gender and my legal gender but not my gender identity or social/lived gender. Do you know which gender you are asking about and why? What does a particular answer to the gender question lead you to assume? Is that correct? People want a) to be represented correctly and b) to be safe.
What are some good practices when asking participants about their gender? Firstly, you need to be clear to the participant what their demographic data will be used for. For my project, I had a couple of sentences at the top of the page explaining about describing samples as we spoke about earlier. This will allow participants to make an informed decision about what to share and alleviate privacy concerns. This is also a good place to reiterate information about anonymity/confidentiality. If you are going to use gender as a point of comparison between groups or it is a stated data point of interest for your study you should say this here. You should ask users if it is ok to quote their answers directly; they may feel safer if you don’t but may also say more if you are.
In terms of the gender question itself there are many points to consider. If the study is only interested in the binary genders, or if you only want data from cisgender people then say so. It is unethical to collect data from people if you aren’t going to use it. Be very clear about what gender you require. If it is just for describing your sample then you’re asking about the actual gender of your participant, in this case you should use a text field with the question “What is your gender?”. If your study size is going to be too large for you to reasonably analyse this field, then a radio button style question is ok; use “Man”, “Woman”, “Nonbinary” as options with an additional “Other” with text field. Never use “Other” without a text field. You may only be interested in your participant’s legal gender, in which case ask “What is the gender on your passport/legal ID?”. Be aware however that this may not match the gender someone is actually living as. Always have prefer not to say if you can.
If there is something specific that is sex or gender related then you should ask that question rather than trying to infer it from a gender field. It’s important to be aware that there is no single test or attribute of a person that can tell you what their gender or sex is. In an interview you may wish to know the participant’s pronouns for reporting purpose so ask that question. Be aware that there are many more pronouns than just “he”, “she” and “they”. Check out http://pronoun.is if a participant gives you a pronoun that you are unsure of how to use.
When reporting the gender breakdown of your sample, if it is small then use “nonbinary” as a catch all. Some participants will give you more specific answers but it may not be safe to report on them if it could single out their data. As an example, as part of a class we were asked to participate in a small experiment. The class size was around 20. I was the only nonbinary person in that class, therefore my data is not anonymous to the researcher. If your sample size is large and genders are often repeated then it is ok to report on them. Say 5 people say they are genderqueer then it is ok to report that, but otherwise roll up single responses into a “nonbinary” umbrella. Again avoid other as it can feel dehumanising to those participants. If all of your participants are male or female, then still report that you had zero nonbinary participants. This helps to normalise the collection of this data. In terms of pronouns, use gender neutral (they) pronouns in your report if you can, otherwise use the pronouns you have been given. Avoid guessing.
Things to avoid
Never have “transgender” as an option in your gender list. A person’s trans status is separate from their gender. I am transgender, but my gender is nonbinary. A trans woman is transgender but her gender is “woman”. A cisgender man is not trans, but their gender is “man”.
Don’t ignore non-binary people in the rest of your questions. I tried to fill out a survey on sexuality recently that allowed me to state nonbinary as my gender but all the questions were framed in terms of same and opposite gender which doesn’t apply to me.
It can be tempted during the analysis phase of your research to see if you can make comparisons between the gendered groups in your sample. If you didn’t state upfront that you were going to do this then you should not. If you are doing this, and did state upfront, then please remember to use the nonbinary participants in your report. I have filled out questionnaires after conferences only to see the report state “There were only a few nonbinary responses so we are not reporting on their answers”. This is very disheartening as I spent time and care filling out that survey only for my response to be tossed. We are a small group and that often means we are statistically insignificant in studies but that does not mean that our responses should not be analysed, particularly in a qualitative study.
I hope that this post is of use to researchers and academics. Please feel free to share this post with people who may be interested. If you have additional questions or want specific advice, please email me at askingaboutgender AT gmail/com.