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13. Stop Using Fill-In-The-Blank Gender Options!
22 Plays17 days ago
How do you ask about gender on surveys and forms without creating new problems?
Fill-in-the-blank gender options often feel like the most inclusive solution. But when organizations try to analyze responses or turn demographic data into action, the reality can be much more complicated.
In this episode of Gender in Focus, we look at what really happens when teams start collecting gender data. We explore why gender questions with fill-in-the-blank are desired by trans and non-binary communities because it feels affirming to have the space to fully describe oneself, especially after being mislabeled for so long. However, this approach may inadvertently make it harder to spot patterns in discrimination, inclusion and employee experience.
We talk through common mistakes in survey design, what organizations need to think about before adding a gender question on a form, and how organizations can balance self-identification with the need for usable insights. You will also hear why being clear about how gender data will be used can increase trust and participation.
If you are designing inclusive forms, running equity, diversity, and inclusion surveys, analyzing demographic data, or trying to understand how different gender groups experience your organization, this conversation offers practical insights grounded in real-world experience.
Topics include: gender data collection, inclusive survey design, non-binary options on forms, demographic questionnaires, EDI surveys, analyzing inclusion data, and building trust when asking personal questions.
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Transcript
Kai's Data Exploration Introduction
00:00:03
Speaker
If you've listened to a few episodes, you probably already know that Kai is a massive data nerd. So we're finally giving him full permission to nerd out because this week we're talking about something that comes up all the time at Transfocus and you've probably
The Complexity of Self-identification
00:00:19
Speaker
seen them before. It's those little fill in the blank boxes when data is being collected. It's something that a lot of 2SLGBTQ people ask for and a lot of organizations are quite keen to use them.
00:00:29
Speaker
um and I think from the clients that we've worked with all the way through to governments, it seems to be like a pretty simple solution um just to let people write things in their own words. But it turns out it's not that straightforward. And Kai, as our resident data nerd, has a lot to say about why these boxes don't always work. um So I'm feeling good about bombarding you with questions today, Kai.
00:00:51
Speaker
How are you doing today? I'm doing fantastic. I'm glad you're ready with all of the burning questions that people have generally or we've seen over the years. And I'm excited to present some of the nuances that are often missing in these types of discussions and just make sure it's on people's radars. Obviously, each situation is a little bit different. So want to respect that, but also just not to jump onto something without considering the consequences.
00:01:20
Speaker
So let's start like ah right at the beginning. When people say fill in the blank, what are we actually
Nuances of Fill-in-the-Blank Boxes
00:01:26
Speaker
talking about? Like, where do we see that show up? Right, yeah, so in case folks haven't come across it or you're not familiar with the the word, whether it's a forum or a survey, there are sometimes options, especially when collecting gender data, where ah there's a kind of allowance for people to fill in the words that they use for their own gender, right? So it's just basically a text box and you can type in whatever. whatever is suitable, whatever is comfortable, whatever is the most reflective of one's gender. And I totally appreciate it, right? Especially for trans and non-binary folks for whom we've been put in the incorrect box, perhaps for years, decades, that can feel really affirming and empowering to use one's own language um when it comes to one's gender. If you're answering that question, you would want to
00:02:25
Speaker
ah respond to it completely, fully and accurately in that way. And so that's at at its basic what it looks like. On a form, it's the same thing. You can kind of write in your own response instead of typing it, but it's essentially the same concept of kind of fill in with your own language.
00:02:45
Speaker
So a lot of people in the community specifically ask for this sort of thing when we're trying to meet certain needs in collecting data. So can you go into a little bit more about why that is so keen and also maybe what is a little bit of an issue with that?
Challenges in Data Processing
00:03:03
Speaker
So Kai has beef with fill in the blank boxes, not to throw you under the bus. So we're going to cause some drama here in the community.
00:03:13
Speaker
a preview of coming attractions here. um Yes. So I, on the one hand, totally get it, right? Like having one's own space just to respond in any way that, or in the the exact way that one identifies, right? And sometimes there's multiple aspects that one wants to tease out, right? It's not just one thing. it's wanting to qualify that in some way, you know. I'm just thinking of an example, like masculine and non-binary person, right? So that that feels good to to kind of clarify and add that nuance and that texture that often comes with gender. And so I in no way fault somebody for wanting that and requesting it.
00:03:59
Speaker
I will say that there's a little more complexity to it. Oftentimes, that is, you know, where we're just looking at the fill in the blank that's on the collection side of things, right? So people are inputting their answers, people are responding in different ways, right? Whether it's trans or non-binary folks, but also cisgender folks are responding in more nuanced ways as well. They're learning about the word cisgender and starting to use it in reference to themselves to clarify, to expand. um Unfortunately, because fill in the blank is so free, people can have responses beyond gender or different from gender. and We've seen all kinds of things. Like, we've done this. That's why we're able to speak from a place of experience, having analyzed on the back end that data.
00:04:49
Speaker
So people say, understandably, i am a human. I get it, right? You don't want to get into gender. Totally fine. and People will say, this is nonsense, right? So they'll be pushing back on the fill in the blank in statements.
00:05:05
Speaker
They'll make um ridiculous things that kind of mock providing So that they'll say, i'm attack helicopter is a very common you know um ah thing online and it gets translated.
00:05:18
Speaker
Some people, they misunderstand the question and they'll respond with their sexual orientation. So they'll say, I'm a lesbian, right? Which, okay, we could probably infer from the use of lesbian that this person is a woman, but it's not a direct response, right? And you're almost having to take another step to make that determination. And that's where we'll talk about the ethics of that type of determination for somebody.
00:05:44
Speaker
Other people will add in. um So because, of course, multiple genders exist and they'll respond to with multiple genders, right? a non-binary man as an example. And so that's where you start on the back end. If you're wanting to um kind of quantify those responses, that's where it gets tricky of like where to put somebody in their responses.
00:06:12
Speaker
So it just gives you some texture of what how people respond to that question, given that you can do anything in that field. And sometimes it's gender and sometimes it isn't. And um there's a lot of complexity to it.
00:06:29
Speaker
And so that's why I have a bit of consideration around it is that... The back end, yeah one is more time intensive ah because there's processing to take what somebody has responded and then figure out how
Ethical Categorization Concerns
00:06:43
Speaker
to quantify it. Because you do want to include it in the analysis of responses.
00:06:48
Speaker
And so that's where we get into ethical considerations of like, we're now making choices as people analyzing where somebody belongs, which they might not have done themselves.
00:07:00
Speaker
Right. Yeah, I really want you to go into that. So in in talking about ethics, what are those ethical considerations? Because I think like when we've talked about this in the past, you've mentioned how the majority of people who are then having to analyze that data are usually or quite often cisgender people. And so they maybe aren't super familiar with this and then suddenly have hundreds of different writing responses. Yeah. And so could you talk about then what what happens on the other side of that and and what the what the ethics looks like?
00:07:33
Speaker
Yeah, absolutely. It depends on the response size to the survey or the how many input points you have. So if it's a survey of 100 people, you might get only a handful of fill-in-the-blank responses. Others will check off, you know, whatever gender categories have been provided.
00:07:53
Speaker
However, if it's thousands upon thousands, if it's a really large survey, um then unfortunately, well not unfortunately, I think it's a very beautiful thing. That's the tragedy of it, right? It's like this beautiful, rich tapestry of people indicating their gender And then um on the back end, um especially cisgender data and analysts without much experience um are looking at all these responses, you know, demigirl and, ah you know, gender fluid, non-binary. mean, there's just so many responses that we've seen over the years and they don't know how to combine those, right? Mm-hmm.
00:08:37
Speaker
And it's easy if it's like just non-binary. We're like, okay, well, we can add that to other ah people who have said non-binary. It's when people are are combining different terms or ones they've never heard of before. Or ah some cisgender analysts may not understand the difference between gender and sexual orientation and then kind of be lumping and making assumptions or determinations on behalf of somebody.
00:09:03
Speaker
um I want people to make that determination for us. I don't want analysts to be involved, myself included, right? couldn't make some of these tough calls either. um i could probably do a little bit better than a cisgender analyst who doesn't have as much awareness, but i am also left with questions and wondering, ooh, like, would this person choose how I'm going to categorize them?
00:09:29
Speaker
And so
Practical Use vs. Detailed Identification
00:09:31
Speaker
part of me, even if it's uncomfortable, wants that to be transparent at the question level instead of left to the back end where we're kind of wrestling and maybe misstepping. or what can also happen is Sadly, um the data is collected and then it just sits.
00:09:52
Speaker
It's not processed. Yikes. So it becomes useless then. It's like no point in even collecting it in the end. I mean, I... i I wouldn't go as far as useless, but it is it's not ah used to analyze the data, how people responded. And so it doesn't translate into actionable, um you know, changes.
00:10:18
Speaker
ah It's usually something where organizations look over the list of responses to say, oh, that's interesting, you know, how people describe themselves. But that's it.
00:10:29
Speaker
It's a data dead end. Right. Right. It just kind of sits there. And I think most people responding to that may not realize that could happen. Right. It's not always the case, but it could happen. And that's, for me, a risk in this type of thing, even though the intention of it is really good. Right. People want to give people freedom.
00:10:50
Speaker
organizations are trying to listen to trans and non-binary folks and respond to what they're requesting. So on all sides, everybody's doing exactly you know what they need. um But unfortunately, it doesn't translate to ah real change, which is for me the tragedy, right? Everybody's doing their best. And it then lands, unfortunately, to what I would imagine are the most vulnerable people.
00:11:17
Speaker
That's the other thing, right? The kicker. It's like, I really would love to make sure that the responses provided by the non-binary gender fluid person do get accounted for, where usually likely struggling with some of or a lot of the systems at play. So that's where I'm like... I'm coming from a good place too where I'm like, we've got to have this data accounted for um in the in the responses. Because I usually analyze the data, um the differences between how people respond, say, have you faced discrimination? I'll differentiate that by you know man non-binary woman and you know if there's a fill in the blank unfortunately those responses if they can't be categorized properly then we we don't know those differences right right which i imagine is super important if we're wanting to make change in in those areas
00:12:17
Speaker
Absolutely. Yeah, because when you do run those kinds of comparative analyses, you can, like, time and time again at TransFocus, when we've done that, you can see a very stark difference between ah trans and non-binary and cisgender, and that's what we're comparing.
00:12:32
Speaker
um Now, there's ways to um handle that. Right, where you put all of trans and non-binary folks together. But if you have a really large sample size, you would want to kind of differentiate trans women from non-binary folks or who I'm kind of putting all in one category, even though it's a very diverse um category. or a set of people and then trans men and even those differences are there there are differences between those groupings right so it's it's really important to be able to see those and unfortunately sometimes that requires creating categories that don't quite fit right the the the richness of of gender
00:13:18
Speaker
Right. So it's it's not that it's about just ignoring what the community is asking for, but it's more about finding that balance of self-identification with the need for data that can actually be used.
00:13:31
Speaker
Yeah. is that what Absolutely. And that's why we tend to, if there is a ah need or a rationale for fill in the blank, it's a matter of separating it from the quantitative side. So you collect the gender and the categories, which always acknowledge, like, these aren't great, right? It's not like we're pretending like these are the best. right They're enough that we can then do those analyses, but then we can also ask a fill in the blank because it would be good to know the different ways that people are describing, right? In case we need to tweak or adjust or update those those quantitative categories. So, yeah.
00:14:17
Speaker
So there is use for it. It's just how you do it that's really important. Right. So, wait, can I just clarify? Sure. So it's just in case you're not aware, data is not my strong suit. So I have questions, personal questions. Yeah, I'm sure many people are in the same boat as you. Mm-hmm.
00:14:40
Speaker
So you're saying fill in the blank is a sort of as well as rather than instead of is that, that what you're saying? yeah Oh, cool. Okay. That makes sense. You definitely could add it into the mix. Now, of course, depending on the organization, i always like the question is whether an organization is ready for the work that is necessary to make this happen. Right. Because a lot of people just focus on the collection side, but don't have any plan or thought for the analyzing side, which can be intensive. And so, okay, maybe we're not recategorizing if we're collecting it as a ah second ah second question, but we're we're still going to have to look at it and kind of... look, you know, and and see what we're going to do because of it. And so there's still some work involved. And so for me, the question is always, i mean, are there resources that an organization can apply to this extra work? And what are they going to do with it? um Because if they're not going to do anything with it, I don't see, don't see it necessary to kind of
00:15:51
Speaker
um yeah, put people in a place of having to provide so much information. So, I mean, the number one question is always, how are you going to use this data? And if not, don't collect it.
00:16:03
Speaker
Right. That was actually my next question. So I'm a bit stumped now, which is that ah what is the first thing that you want organizations to to think about before adding any kind of demographic question, I guess. And so aside from...
00:16:19
Speaker
what are you doing with this information? Let's say they do want to use that information for whatever it is that they want to use. what What should organizations consider? Because obviously they're kind of in a bit of a position here where the community are asking for one thing, but the need, but the the way that they can actually interpret that data is a bit stumped with this.
Building Trust Through Transparency
00:16:39
Speaker
And so what what should they do then? What's what's next Yeah, you're you're so right in terms of painting painting the picture of the organizations often feel like they're in a bit of a pickle, right? Right. They want to do right by trans and non-binary folks, particularly given the challenges. And they're like, I don't want to add more challenge by going against what they're requesting.
00:17:02
Speaker
And that's why a thoughtful process is so important. So it's not just like we're doing a survey and then madly scrambling at the last minute to ah figure out what gender question, if at all, to ask. It's to have a thoughtful process to be, kind of explore the options because there are a few, not just the fill in the blank or, um you know, the categories that we've talked about, but explore the options and then Based on the needs or the resources or the outcomes needed, you make a determination and then you're able to explain it to folks.
00:17:42
Speaker
Because I don't think um in many instances that I've been a part of, There are, if you explain things well, like why you went for a particular thing or didn't, or you're not collecting, and you're able kind of to bring people along. And right actually, I find that trans and non-binary folks, not everyone, obviously, but a lot of them, If you explain it to them like, oh, okay, that makes sense. You're doing this so that you can hear better about what our experiences are and with the ultimate purpose of actioning them. Okay, fine. right Cool. Let's go. Right? So in fact, they may trust you more because you've been very thoughtful about it and um know what you're getting into, have a plan for it and, you know, maybe even going to circle back to the community to explain the results, you know, so that kind of thing can really be a game changer to be like, oh, okay, you're on our side, you're not wanting to kind of dismiss us or work against us, which, to be fair, a lot of trans and non-binary folks have that experience of just being cast aside. So it can come from that initial response, thinking that that's at play.
00:18:57
Speaker
And then if you explain it well, in if ah even if it's different from what they requested, um they will kind of like, who okay, i can I can relax into this experience, right?
00:19:10
Speaker
That's so true. Oh, my goodness. I've seen like ah many forms i filled out have either ah not had a non-binary option or just had fill in the blank. it was It's like it's such a there's like nothing in between. And so I don't know. i feel like if I'd had something explained, like how they're going to use the data and why it is only non-binary and not making space for, I don't know, gender fluid or whatever it is. um I think that would make so much more sense. I'd feel a lot more trust in the people I'm giving my data to, like my information to. I would feel a lot more secure in that if I knew why there were challenges in the first place and why it's so restricted and also how this data is going to be used in the first place and like for the purpose of it. I feel like that would make so much sense. Do do you get sorry, I'm kind of so going off in a direction here. But do you get organizations that are a bit hesitant to explain the shortcomings? Like, I'm imagining that puts them in a bit of a difficult place where they kind of don't want to admit that there's an issue, whereas actually, it does the opposite thing in my mind of creating that trust.
00:20:19
Speaker
Absolutely. And a good point about trust. We hear that so often from, ah you know, other parts of the trans and non-binary community is just like, just explain it to us, you know, don't leave us out in the dark trying to figure it out ourselves and wondering too, because of course we've had a lot of bad experiences, so we can go to a negative assumption, right? um under Understandably so.
00:20:46
Speaker
um But to your point about, um now I forgot your question, shoot.
00:20:53
Speaker
Organizations feeling, it's lucky I can remember it. It's very unusual. ah It's organizations who maybe feel a bit hesitant to share that there are shortcomings with the way with the way that they're collecting that data.
00:21:04
Speaker
yeah Yeah, especially ah larger organizations or more formal ones, the kind of opening up ah to the inner workings feels like risky or vulnerable or um people are going to attack us for it. But I will say that more often than not, it's actually um smooths the process along, you know, and just brings people along and it doesn't actually reduces risk rather than creating risk. And so that may be a bit antithetical and a bit of a surprise for folks, but we find people are really appreciative. Sometimes at the end of surveys, we'll have like, you know, final thoughts and they're like, thank you so much for this survey. It was just so easy to take it. And I kind of understood at every step what was happening and, you know, i felt brought along and, you know, they just kind of wax on and on. You don't get that typically in a survey that people are... excited about taking it and and feel like seen and supported as part of the process. And so I definitely invite organizations to be more transparent about that.
00:22:15
Speaker
You know, I get that there's things to weigh depending on the context, but the more that you can share, the better. And the more likely somebody is to take the survey at all, right? If there's any whiff of nonsense, like like trans people are out of there. Just because, like you said, we've come across so much and it's just like, ugh, this again.
00:22:38
Speaker
But explanations go a long way to reassuring folks that have had typically a pretty bad experience in other places.
TransFocus's Role in Data Strategy
00:22:48
Speaker
what's the process been like um when organizations come to trans focus to kind of look through this stuff Yeah. So we do offer this type of support and thinking through how to ask, what to ask, if to ask, you know gender data. Sometimes sex at birth is at play as well. And that's tricky.
00:23:11
Speaker
And so it's really good to think that through. This comes off comes up often in a healthcare context. But it can also sometimes in an educational context where you know birth certificates are part of the registration process. So there's so many different factors when it comes to collecting this type of data, whether there's a sensitivity aspect if you're collecting sex, which can be painful or uncomfortable for trans and non-binary folks to provide. um And then also the gender data collection
00:23:45
Speaker
And we go through a bit of a process of of asking key questions, understanding how it's been collected in the past or currently, and then what is possible going forward, understanding you know what the outcomes that are necessary. Are you trying to change programming or is this for doing data analysis to understand how different genders are experiencing you know you know, different social social cultural determinants of health and on and on. So we just want to work through that.
00:24:22
Speaker
Oftentimes, organizations will look at what government is doing and want to align with that. And for many, in many respects, I understand because you'll want to compare against that data to see where you stand as an organization relative to the general population. i get that impulse. However, depending on the government, it how it's collected, may not be suitable for one's organization. And so just to be a little bit thoughtful before boldly going forward. And we have just kind of a decision-making framework or process that we undertake to kind of balance those trade-offs and then come to ah a place. And we can also help with communicating, you know, how this was developed. There can be frequently asked questions or questions
00:25:16
Speaker
you know Even sending out emails, we can review all of that or help templates to to make that a smoother process. Because it's not just about the questions themselves, it's the kind of all the stuff around it as well. So we help out with that or just communication strategy in general. So just kind of from beginning to end are able to help with that. in In certain circumstances, we're also pulled into data um analysis as well.
00:25:44
Speaker
So interpreting the data at the back end. Fair. Is there anything else that I haven't asked you that you need that you need to answer? Get off my chest regarding fill in the blank. Yeah. Any fights you want to start? Like, okay. Any drama? Data drama?
00:26:03
Speaker
um No, just just saying that for the people who are listening for whom fill in the blank is important, I get it um And I understand why that is such a nice experience. So I don't want to discount the user experience side of things. um I just want to nuance it a bit with what happens on the backend and express how we've tried and, you know, um it through many different surveys that we've done, because we really wanted to see how that could be possible, right? So it's just not just wholesale discounting it, but just, but okay, let's try it. um And then having a lot more difficulty in pulling that off.
00:26:45
Speaker
And so just wanted to people to be aware of fill in the blank in general and um hopefully ah see the need for the quantitative. But we can do combination of the two. So, but just keeping them separate as well.
00:26:59
Speaker
Yeah, just some food for thought as you go through, whether you're an organization or an individual. Hopefully that helps just shed a bit of light on this this topic. Like, Amazing. Thank you so much, Kai. I hope you enjoyed an opportunity of what, half an hour of rattling on about data.
00:27:19
Speaker
Thank you for the opportunity. And of course, always look forward to talking to folks more on the topic if you want to go deeper. There's more to it, surprisingly. But we decided just to focus on fill in the blank first. so Sweet.
00:27:36
Speaker
Well, thank you so much and see you next time. All right. Bye for now.