Contents
- Q1. Identity words
- Q2: Titles
- Q3: Pronouns
- Q4: Family/relationship terms
- Meta
- Some of the questions this survey seeks to answer
- This year in review
- Closing thoughts
- Footnotes
- Support me!
- Links to files
Welcome to the eleventh Gender Census annual survey report! This year we broke the participation record by about 4,000 people.
The survey lasted about a month, taking place between 13th May and 17th June 2024, with 48,645 usable responses.
The usual caveat: It’s a community-based project run by an enthusiastic volunteer, and none of it is not affiliated with any organisations, companies or academic institutions, so it was promoted entirely on social media and by word of mouth.
Before starting the survey, participants were required to check the following two boxes:
- Yes, I confirm that I don’t really fit into just one of the two boxes of “always, solely and completely a woman/girl” or “always, solely and completely a man/boy”.
- Yes, I understand that I can back out of the survey at any time before the end and my answers won’t be counted, and I understand that if I complete and submit the survey my anonymised response will be made publicly viewable.
You can see a summary page of the big three questions here.
Q1. Identity words
Participants were asked: Which of the following best describe(s) in English how you think of yourself? There were 19 identity word/phrase checkboxes, plus none / I do not describe myself and questioning or unknown. Underneath the checkboxes there were 20 textboxes that invited participants to type extra words not otherwise listed. Checkboxes were randomised to reduce primacy and recency bias. This question was optional, and participants could select as many checkboxes as they wanted to.
Checkboxes
Content note: Some of the words in the checkbox list are often used as slurs against the LGBTQ+ community.
Here’s our top 5 this year, and how they compare to last year:
- nonbinary: 63.1% (down 2.7%)
- queer: 54.8% (down 1.2%)
- trans: 46.7% (down 2.0%)
- a person / human / [my name] / “I’m just me”: 42.5% (down 3.4%)
- transgender: 40.3% (down 1.5%)
Why are we even here, if not for a bar graph? Here you go:
It’s time for the annual rainbow spaghetti. Here’s the top 10 words for the 30-and-unders compared to the 31-and-overs:
The entire top 10 list was less popular compared to last year, and I don’t know for sure why that is. One theory is that the highest percentage of participants ever were over the age of 30, and older participants tend to choose fewer identity words, which could reduce the percentage of everything a little bit. It’s also worth noting that the top identity checkboxes were also higher across the board last year, so perhaps it’s not significant and this is just everything regressing to the mean.
Here’s our top 10 since 2015:
I loooooove that we have a whole decade of data to digest in the trend graphs now. Here’s my thoughts:
- There’s nonbinary up at the top, comfortably hovering between 60% and 70% since 2015. This year is the lowest it’s ever been, but it’s only 0.2% lower than that dip in 2018, so I’m not sure how meaningful that is.
- Queer (red) shot to second place when it was added to the checkbox list in 2019. It went down a little bit this year like everything else, but even so the gap between queer and nonbinary is still closing. Queer is definitely one to watch.
- Genderqueer and genderfluid have been pleasingly consistent, and trans, transgender and gender non-conforming have been gently climbing throughout their time on the checkbox list.
Enby is interesting enough that it gets its own mini-section. Here’s that graph again, with enby emphasised:
I had started to suspect this last year, but this year I’m a little more sure that enby might have peaked in 2021. Nothing else in the top 10 is this shape on the graph, and this shape is what I’d expect to see from a word coming into fashion and then leaving again. It is hard to be sure, since everything went up last year and then came back down this year, so perhaps next year will be more revealing.
Aside from the popularity trend, something else I immediately noticed is in the “<=30 vs. >=31” diagram above. Enby got 29% among the 30-and-unders, and 31% among the 31-and-overs, which is to say, it was more popular among older people.
I have previously looked into whether enby is connected to age. It was originally coined as an alternative to boy and girl in words like boyfriend and girlfriend (i.e. enbyfriend), a phonetic spelling of the abbreviation of nonbinary:
- Nonbinary → N.B. → enby
In 2020 I explored any connection between enby and age using the 2020 survey’s data. At the time it did appear that younger people were more likely to choose enby, and the shape of the data was more like that for boy and girl than for man and woman:
The bolder lines in the above graph are enby, boy and girl, and they all start higher (more popular) in the younger age ranges and gradually decline.
It’s not possible to confidently replicate that this year, because man, woman, boy and girl weren’t checkbox options this year and that could skew the data in interesting ways. However, we can make a graph comparing 2020 and 2024 results for enby by age group:
Enby in 2020 is (more or less) a diagonal trend line starting higher in the lower age ranges, showing a pretty clear “enby = young” correllation. But 2024 is another story. Enby peaks around ages 31-40, and then has another peak in age 51-55! The trendline does still point roughly downwards this year, but I’m not convinced that that’s as significant as it looks, because older participants tended to select/enter fewer identity words anyway.
So, again, more data needed, but I have a strong suspicion that kids nowadays are just not using enby as much.
Write-ins
This year there were 14,147 unique textbox entries, of which 2,709 were typed in more than once. That’s one new word for every 3.4 respondents, a big drop compared to last year’s new word for every 2.3 respondents.
Here’s our top 10 textbox identities:
- dyke: 4.5%
- (a) girl: 3.6%
- creature: 2.0%
- (a) tranny: 1.9%
- (a) guy: 1.6%
- genderfuck + variants: 1.4%
- tran(s)sexual: 1.3%
- lesbian: 1.3%
- entries that start with “boygirl”: 1.2%
- (a) man: 1.2%
Dyke was on the checkbox list in 2023, but was removed for this year. In my experience, it gets typed in a lot when fag is on the list, and fag gets typed in a lot when dyke is on the list – and when that happens there tend to be feedback comments like “how come fag is on the list but not dyke?” and vice versa. I do have a rule of including “opposites” on the checkbox list for fairness, but at some point in the past I did a few polls to find out if people felt that dyke was the opposite binary gender to fag and there was no clear consensus, so I tend not to think of them as a pair these days.
Creature is… a meme? Did I get that right?
[Edit: I have been informed by some participants that they intended it in an inhuman/otherkin kind of a way!]
So, I got curious about whether some of these were tied to any age trends. I made some graphs, omitting age groups that got less than 100 respondents. Those of you using screen readers will probably need to see the table of data on Google Sheets, here.
Comparing tranny and trans(s)exual:
I was surprised to see that they didn’t really match up, and intrigued to note that it’s mostly the young’uns reclaiming tranny.
The creature graph is almost exactly the same shape as the tranny graph, and the numbers are almost the same too. It’s like creature is tranny shifted 5 years older. And I’m including dyke here because it was the most popular write-in, but I don’t have any commentary, I just thought I should include it for completeness.
Moving on to something a bit meta: the number of identity textboxes provided and used. In 2023 I increased the number of identity textboxes from 5 to 20, and about 1.4% (560 people) used more than 10 of them. There were 20 textboxes this year too, and fewer than 1% (303 people) used more than 10 of them. Can we get a graph of that, please?
Even at 20 textboxes I get some people in the feedback box complaining that there weren’t enough! So I think, going on the numbers alone, next year I might make it 10 textboxes, just to make the data a little bit easier to process. The vast majority of people will be able to enter all the words they want to enter, and a small proportion will be able to enter most of their words.
Overall
The average number of identity words chosen was 5.9.
3, 4 and 5 were all within 0.4% of each other, it was really close. As usual, as age increased the number of identity words decreased. This has been the case since I started collecting data on age. This year I decided to break it down further:
Generating the checkbox list
Content note: This section refers to words that are sometimes used as slurs against LGBTQ+ people.
This year was the second using the new system for the checkbox list, which is designed to generate a good manageable list of terms that are representative of participants from a broader age range.
Terms new to the checkbox this year were:
- bigender – 5.7% as a checkbox, 2.5x more popular than when it was a textbox entry last year.
- butch – 9.8% as a checkbox, 4.3x more popular than as a textbox entry. Butch has joined and then left the checkbox list before; last time it was 5.3x more popular as a checkbox.
- demiboy – 6% as a checkbox, 3.5x more popular than as a textbox entry last year. Demiboy has also joined the checkbox list before, and last time it became 6.4x more popular as a checkbox.
- demigirl – 7.1% as a checkbox this year, which is 3.6x more popular than when it was a textbox entry last year. Demigirl has also joined the checkbox list before, and last time it became 7x more popular as a checkbox.
The following were removed from the checkbox list this year:
- dyke – it was added to the checkbox last year and became 3.7x more popular as a result, but it was then immediately removed thanks to the new multiplier system for selecting checkbox terms. This year as a textbox it only dropped by a bit over half.
- man – removed for the first time ever this year, and it dropped from 16% as a checkbox to under 1% as a textbox entry. Oof. It did make the top 10 in the write-ins list though.
- woman – also removed for the first time this year, and it dropped in a similar way to man, from about 15% to less than 1%. It made the top 20 in the write-ins.
This is all within the realm of expectation. Generally, terms leaving the checkbox list lose a lot more popularity than terms gain when added to the checkbox list. It seems like when this “multiplier” is quite low and about the same in both directions, that term tends to yo-yo on and off the checkbox list year on year.
So, how about next year?
For the last two years I’ve taken the top terms from both the 30-and-unders and the 31-and-overs to generate the list. This year I was meandering through the spreadsheets and wondered if it was within my attention span to made a spreadsheet that would do the same thing but taking into account every 5-year age group individually, and what the checkbox list might look like.
In theory it is more fair, because even within the 31-and-over group there are age groups that aren’t as well-represented because they have far fewer respondents. Here’s a graph to show you what I mean:
In the graph above, the participants aged 31 and older are the purple bars. This year is the highest proportion of 31-and-overs that we’ve ever had, and it’s still only about 21%. Within that group, only 8% were over 50 (2% of the entire surveyship, it’s a word, honest). So when I include top words from the whole 31-and-over group, I’m still really only representing the 31-50 year olds.
It turned out that making a similar system that took into account each 5-year age group was possible, and the provisional list for next year looks like this:
- a person / human / [my name] / “I’m just me”
- agender
- autigender
- binary
- cisgender
- dyke
- enby
- fag
- gender non-conforming
- genderfluid/fluid gender
- genderqueer
- nonbinary
- none / I do not describe myself
- queer (in relation to gender)
- questioning or unknown
- tranny
- trans
- transfeminine
- transgender
- transmasculine
I’ve bolded the new words, which are dyke, tranny and autigender. Dyke is one of those words that yo-yos on and off the checkbox list because people have been typing it in even when it’s not on the checkbox list; it made it onto the list by being close enough to the top in every age group between 16 and 35. Tranny has made it onto the list mostly because of the participants under the age of 25. And autigender has been creeping up the list for a few years; this year it’s on the list because of the 46-50 and 51-55 groups, and I think that makes sense, because the older you get, the better your chances of having worked out you’re autistic.
Four words will be lost from the checkbox list next year: bigender, butch, demiboy and demigirl. Yes, those are the four words that got added this year. Hm. I’m putting it down to a combination of low multipliers and the new selection method. But, fingers crossed, hopefully this means people from every age group are more likely to see something that represents them in the checkbox list next year.
A quick note on the future of the checkbox list
You might remember me wondering aloud last year about how long the checkbox list should be. I settled on “about 20”, and made a judgement based on how many checkbox terms were being missed and written into the textboxes instead. I am pleased to report that it seems to be working – queer is the first checkbox term in the textbox list and it just about made the top 40 with just over 300 entries, and all of that is pretty good compared to the days of yore when the checkbox list was much longer. So, I’ll continue to aim for about 20 identity checkboxes.
Also, based on some tinkering and some thinking, I’ll use the median multiplier calculated from only adding identity words to the checkbox list, not removing them. That’s because the multiplier seems to be very different when removing compared to adding, and as we’re calculating from a place of deciding what to add to the checkboxes that will hopefully give the most accurate results.
Q2: Titles
Titles (with name)
Participants were asked: When someone writes “Dear [your name]” at the top of an addressed letter/email, what title would you want someone to use when writing to you, if any? There were several specific titles to choose from, plus some hypotheticals, no title at all, unknown, I choose on the day depending on how I’m feeling – and a new option, a title not listed here. All of these were presented as radio buttons (one answer only) to mimic the “filling in a form” context, and the order was randomised to prevent primacy and recency bias.
Here’s what the top 5 looks like:
- No title at all: 42.2% (up 2.1%)
- Mx: 17.4% (down 1.3%)
- Mr: 11.3% (down 0.2%)
- Non-gendered professional/academic title: 9.2% (down 0.2%)
- Ms: 5.8% (up 0.3%)
That’s the same titles as last year in the same order, and very little change to report.
The first thing to note from the list of all titles is that Ind has dipped below 1%, which under the current system means it should be removed from the checkbox list. More on that later.
Here’s our graph of ongoing trends:
The top two lines are No title at all (blue) and Mx (red). Mx was holding its own for a while there, but this year the gap between no title and Mx has increased again. And Mx is barely above Mr, too. I know I’ve said it before, but being able to see linguistic trends in real time year after year is super cool, isn’t it??
The titles getting under 15% are very difficult to tease apart in that graph, so here’s another that’s a bit clearer:
The climb of no title and the fall of Mx are both still pretty striking, but we can also now see that binary-gendered titles Mr and Ms have been increasing in popularity, as have non-gendered professional/academic titles such as Dr.
Of the people who chose a title not listed here, results are incredibly close to last year. First of all, 2.2% of all participants chose it, which is basically the same as last year. And the two most-entered titles were M and Mistrum, and the percentages below were also almost the same as last year.
- 14.7%% (0.3% of all participants) entered M, and most intended it to be pronounced as the letter M, “em”. Most people entering that title (41.7%) said that it was a gender-inclusive title that anyone of any gender can use.
- 9% (0.2% of all participants, a bit lower than last year) entered something involving the word Mistrum, which was mostly abbreviated to Mm but also often Mt. 74% categorised it as a gender-exclusive nonbinary title, “typically used to express any nonbinary gender”, which is quite a lot higher than last year.
Titles seem much slower to shift than identity terms, and they seem to be particularly affected by culture. If you’re planning to make any big decisions about titles, especially if it’s to do with form design, I recommend grabbing the spreadsheet of all responses and removing all responses except those from your country. That should help you to get a good, representative picture of the nonbinary people in your part of the world.
Choosing the titles (with name) list
So, as I mentioned above, Ind has dipped below 1%. That’s been quite a gradual decline, so I haven’t really had to think about it much for a while. I think 10 (plus “a title not listed here”) is a pretty good length for the title list, and if I remove Ind that’d leave space for something new to be added to the list. Based on the textbox entries that’s M, so I’ll add that next year and get those two multipliers to get the ball rolling. From next year, perhaps I will implement an age-based automatic option selecting system like I have for identities and pronouns.
Titles (without name)
Participants were asked: When a stranger addresses you and they don’t know your name, what title(s) would you want someone to use, if any? This question is here because of the fairly consistent question from USians, “what’s the alternative to sir/ma’am?”
Participants were able to choose as many options as they wanted, and answer options were presented in a randomised order to prevent primacy and recency bias. The question was optional.
Here’s the graph of checkbox options:
And here’s some more specific stats for the top 5:
- No title at all: 64.9% (down 4.4%)
- Friend: 35.0% (up 2.8%)
- Sir: 33.2% (down 3.3%)
- Comrade: 24.1% (new checkbox; multiplier 11)
- Mx: 20.6% (down 2.7%)
New to the checkbox list this year were comrade (2.2% in the textboxes last year) and questioning or unknown. I added comrade in case I start using a multiplier system to add and remove checkbox options, and this time it was 11. Questioning or unknown was a corrected oversight, it was a new question last year and I just accidentally forgot to include it.
Slightly behind comrade in the textboxes last year was dude with 2.1%. It got 2.1% in the textboxes again this year. I don’t know if that coincidence means anything but it’s fun. I haven’t yet decided if I will add it to the checkbox list. Kudos to the dudes for their consistency.
Pressure to add a titles-without-names question to the survey primarily came from people in the US who live in regions where addressing people as “sir/ma’am” is near-compulsory etiquette. I suspect comrade and dude is not what the more progressive, nonbinary-inclusive Southern belles were expecting.
I’ve made a new sheet here for tracking these kinds of titles over time, but it only has two years of data, so just bookmark it and set a reminder to revisit in 5 years or so…
I wondered if title preferences might be affected more by country than by age, so I made this graph:
This really brings home how strong the majority is for no title at all. It’s way ahead in all five countries, with well over half of participants choosing it, and nothing else got more than 40%. Having said that, 40% is still pretty decent and cannot be dismissed.
There’s less variation than I was expecting. I am surprised by the UK’s different attitude to comrade, I didn’t realise it was received more favourably in other countries. The USA and Canada are quite similar, which I think makes sense due to their cultural similarities and geographical proximity. There’s often a lot of reponses from Germany and they’re a bit of an enigma to me because I have no cultural context for them, so I’m never sure what to make of it. (Hi, Germany! Thank you for coming!)
So then I decided to compare with age:
There’s a lavender blue spike on some of the graphs that suggest that nonbinary ladies and gents of a certain age (66-70) really like to be called sir, miss, ma’am or madam. However, it should be noted that above age 60 the sample sizes start to get quite small so the data might be less reliable.
It looks like older people were less likely to say they were happy with most of the titles overall, but they were also fairly unlikely to choose no title compared to middle age groups. This makes me curious to see how many titles people were choosing overall, so:
That explains it! Older people were choosing fewer options in that question overall – but then there’s those ladies and gents of a certain age (66-70) choosing more options each for reasons beyond our ken.
Last year I didn’t advocate for just avoiding sir/ma’am and any other similar forms of address altogether, because of societal/cultural differences and so on. I think I stand by that, because there are even some areas within countries where they’re borderline compulsory even when the country overall doesn’t really use them. But I don’t stand very firmly, because I don’t have a lot of experience of any culture other than my own. (I’m in the UK, and we pretty much never say sir or ma’am.)
I recommend that you copy the spreadsheet of responses and then remove all except responses from your own country. That will give you a more representative view of language preferences in your area.
Q3: Pronouns
The pronouns question was a little different this year.
The part that is the same as usual: Supposing all pronouns were accepted by everyone without question and were easy to learn, which pronouns are you happy for people to use for you in English? Participants could choose as many of the 15 randomised checkboxes as they wanted. Checkboxes included 11 common and uncommon pronoun sets, plus non-pronoun options like “any”, “avoid pronouns”, and “questioning or unknown”.
One of the checkboxes is “a pronoun set not listed here”, and if you choose that it takes you to a second section where you can enter up to five new pronoun sets in detail.
The new part: A question about how you want people to use your pronouns. There were six radio buttons, so you could only choose one, and one of them was “other” plus a textbox to specify. As this was a new question, I put a comment box underneath.
All questions about pronouns were optional.
Checkboxes
Here’s our bar graph:
The top 5 pronouns (or lack thereof) were the same five in the same order as last year and the year before:
- They – they/them/their/theirs/themself: 75.5% (up 1.0% on last year)
- He – he/him/his/his/himself: 42.0% (down 0.5%)
- She – she/her/her/hers/herself: 36.0% (up 3.3%)
- It – it/it/its/its/itself: 20.3% (up 0.9%)
- Avoid pronouns / use name as pronoun: 13.9% (up 0.7%)
10.9% of people weren’t happy to be called they, he or she, which is a little bit lower than last year.
Here’s how the pronouns are looking since 2015:
That blue line at the top is they/them, and the lines below it are he/him (red) and she/her (yellow). They/them has been fairly consistent over time, fluctuating by only about 6% since 2015. He/him and she/her have been gradually increasing in popularity this whole time.
Here’s that same graph with they/them, he/him and she/her removed, so that you can see the remaining pronouns (under 20%) more clearly:
Most have been very steady over several years, and even it/it hasn’t really changed much since last year. (I had wondered if it was going exponential, overtaking all pronouns by 2028. Perhaps by 2035 replacing all nouns too, and even some adjectives.)
Here’s the top 10 for each age group:
The main thing I’m noting is, this year is the first year without “mix up my pronouns” and “my pronouns vary”. So there are more pronoun sets in the top 10, namely ze/zir and fae/faer. Usually, with mix it up and variable, everything below he/him and she/her is a lot more tangled up. Now they’re gone things are matching a bit more between the two age groups, in that there are more straight and straight-ish lines. (So that was probably a good call – clearer data is always a win.)
As I’ve noted above, you can see that the older age group is selecting fewer pronoun sets. (#2 on the left has a higher percentage than #2 on the right, etc.) The main exception is they/them, which has gone from being more popular among younger age groups to being more popular among older age groups, like so:
Last year I had noticed this, but it was too soon to say anything for sure. This year the gap has widened by another percentage point and a bit. I am curious for next year’s results, to see if this continues.
This graph got me thinking though – now that I’ve been asking about age for five years, we can start making more detailed graphs about specific pronoun sets and see how things are shifting over time and with age. After a little bit of back and forth on Mastodon and Tumblr, I/we came up with this:
In 2020 there were 69 percentage points between the highest and lowest popularity percentages for they/them. The older age groups were a lot less likely to use they/them, and generally speaking the younger the participant, the more likely they were to go by they/them. (The group most likely to go by they/them was 21-25, with 80.9%.)
Now, only 5 years later, that difference has almost halved to 37%. In short, the older age groups are “catching up” to the younger ones. But at the same time, younger age groups are becoming less likely to use it:
The drop in younger age groups isn’t as big as the climb among older ones, and it’s too soon to say whether this is a trend that will continue or if it’s just a blip. But still, interesting! I’d really like to compile the same stats for it/it as well, because I think the age difference will be even more extreme. (This section is long enough already though, let’s keep things moving.)
As in previous years, people in the older age groups are choosing/entering fewer pronoun sets each. Despite only 28% of participants having filled in the Gender Census annual survey before, the graphs for last year and this year are almost identical:
[People using screen readers can see the tables of stats and the graphs here for 2023 and here for 2024.]
Spot the difference? (No, me neither.)
Anyway, that’s most people aged 30-and-under choosing two pronoun sets, and most people 31-and-over choosing just one. The average (mean) number of pronoun sets chosen overall was 2.2, the same as last year. Here’s how that looks on a graph since 2016:
Neopronouns
We have a very respectable selection of neopronouns in the checkbox list now, which look something like this:
- Xe – xe/xem/xyr/xyrs/xemself: 8.8% (down 2.2%)
- Fae – fae/faer/faer/faers/faeself: 6.2% (down 0.3%)
- Ze/zir – ze/zir/zir/zirs/zirself: 5.0% (new this year)
- Elverson – ey/em/eir/eirs/emself: 4.3% (down 0.7%)
- Ae – ae/aer/aer/aers/aerself: 3.8% (new this year)
- Spivak – e/em/eir/eirs/emself: 3.6% (down 0.3%)
- Ze – ze/hir/hir/hirs/hirself: 3.2% (down 2.0%)
None of them were selected more often than any of the established pronouns (they/them, he/him, she/her or it/it).
There is another way we count the neopronouns. When a participant selects the checkbox “a pronoun set not listed here”, they’re guided through a separate section where they can enter all 5 forms of up to 5 neopronoun sets. There are example sentences with fill-in-the-blanks, to help ensure that we get accurate information that can be counted easily.
7.8% of respondents opted to enter at least one neopronoun set, which is quite a lot lower than last year. Respondents were overall a little bit older than last year so perhaps it’s not surprising; this year the 31-and-older group were less than half as likely to select that custom neopronoun checkbox, which is in line with previous surveys.
The most popular write-in neopronouns this year got 0.3%. Even though the most popular write-in neopronoun changes most years, it almost always gets 0.3% for some reason. This year it’s star/star/stars/stars/starself (singular verbs), which was the most common spelling of star/star, and here it is in conversational use:
I’m in a coffee shop with my friend Sam. Star is buying starself a coffee in stars reusable takeaway cup. “Is this your coffee?” the barista asks me, holding up Sam’s coffee. “No,” I reply, pointing to Sam, “it’s stars. I’ll take it to star.”
The next most popular write-in pronoun was they/them, which… it’s complicated. Some people probably just didn’t see the checkbox option, which can’t really be prevented. Some like they/them and have regional or cultural variations in some of the forms, like theirself for the reflexive, or singular verbs (“they is a dentist”). Some people are very used to they/them as a plural (used for referring to groups) and it feels more natural for them to say themselves even when referring to one person. And some dislike the reflexive themself because they’re plural/have DID.
2,552 unique pronoun sets were entered this year (based on subject/object/reflexive only), which is one new pronoun set for every 19-ish participants. Of those 2,552 sets, 562 were entered more than once.
How people want their pronouns to be used
This was a brand new question this year, and it looked like this:
Answer options were randomised and you could only select one.
From a data point of view… honestly, it’s been an absolute nightmare.
I’ll start with the traditional bar graph:
When we combine “there are no rules” and the people who left the question blank, that looks more like this:
But I have serious doubts about whether this question’s statistical output is at all reliable. 3,623 people used the “other” textbox to tell me about their specific situation, and most of it is totally unquantifiable.
Let’s get into that.
So Cassian, why does the question say you can leave it blank if there are no rules, and then also offer a radio button to specify that you have no rules? Isn’t that a bit redundant? Oh yeah probably- oh wait…
- “Always ask if unsure”
- “Any and all pronouns are acceptable as long as malice is not the intent”
- “Any of the ones I picked work in any combination”
- “Any of the pronouns I use are fine.”
- “As and when”
- “As long as people are being respectful I’m not particular about pronouns”
- “at the moment people can call me what they assume I am (she) but I want it to be respected if that were to change”
- “Blank” (two definitely different people skipped the “there are no rules to my pronouns” button to literally write “blank” into an optional textbox)
- “Call me what you want”
And that’s just partway into the Cs. Wait ’til you get to the Is:
Oh well that’s not so bad-
I mean, okay but it’s quite easy to sort and count those-
All of those people saying they don’t care what pronouns people use, when there was a radio button right there saying there are no rules about your pronouns, AND a note saying you could skip the question! I threw together some quick formulas and found 214 starting with some variation of “I [do not/dont/don’t] [really] [care/mind/give a]” and 30 starting with “whatever”, and I’m sure there are plenty along the same lines that I missed.
And there are over 3,000 “other” textbox entries to sort through! The ones that aren’t a radio button answer slightly reworded or just restating the pronouns they told me in the previous question are often a very specific and wibbly-wobbly rule that works in real life but in data terms cannot be categorised. That’s completely allowed and what I was hoping for, and I don’t want anyone to feel bad for what they wrote into the textbox here or anywhere else, but we’re looking at hundreds (or maybe thousands) of totally unique rules. There were so many unique responses that the query I wrote to process them kept breaking Google Sheets in such a way that it thought I wasn’t connected to the internet anymore??
To be fair, some of it is stuff that switching from a radio button (one answer only) to a checkbox (multiple answers allowed) would fix. That’s things like, people complaining that their device wouldn’t let them unselect something, or people who want something that kind of straddles two options, etc.
But beyond those few, that leaves many, many answers that are completely unsortable. The sheer quantity of people skipping the useful pre-written answers to use the “other” textbox makes the statistics associated with the pre-written answers a lot less reliable. Usually I would put it down to a need for better survey design, but I genuinely cannot think of a way to change it so that the data is both reliable and tidy. I could spend weeks/months trawling through these answers and come up with dozens/hundreds of checkboxes, and some people would still need an “other” textbox, and a bunch of people who don’t need it would still use it to write the gender equivalent of the kind of thing you get at the start of a recipe blog post before you get to the actual recipe.
Basically, I have learned two things:
- This question’s answers are too nuanced to fit within the Gender Census’ scope of providing very broad quantitative data on language preferences;
- People are bad at survey. ✦
Considering the type of data the Gender Census survey is aiming to collect, I think the solution is to simply not ask this question at all. Which, considering how different everyone is in terms of pronoun rules, seems… fine? Like, perhaps asking/explaining a lot will just be the social convention, or in 10 years I’ll check in and a best practice or new strategy will have emerged. I’m cool with it, but… blimey. It was like when a cartoon character takes one thing out of a stack and the whole stack falls down on top of them.
Pronoun checkbox selection method
This year I added two pronoun sets to the checkbox list to get their multipliers, so that I can start automatically choosing the pronoun checkboxes in the same way that I do with the identities. This has given us:
- ae/aer/aer/aers/aerself (singular verbs) – 5.8x more popular as a checkbox
- ze/zir/zir/zirs/zirself (singular verbs) – 17.2x more popular as a checkbox
(The spreadsheet to keep track of the pronoun multipliers will live here.)
That’s all we’ve got to go on, but it’s a start. Let’s take the average of the two, 11.5, and use that as a multiplier for next year. Applying this to the write-ins, taking the same number of top pronouns from each age category, excluding anything entered only once in that age category, and limiting to 15 checkboxes, results in this list:
- Any
- They – they/them/their/theirs/themself (for referring to an individual, e.g. “they are a writer”)
- He – he/him/his/his/himself
- She – she/her/her/hers/herself
- It – it/it/its/its/itself
- Xe – xe/xem/xyr/xyrs/xemself
- Fae – fae/faer/faer/faers/faeself
- Ze/zir – ze/zir/zir/zirs/zirself
- Elverson – ey/em/eir/eirs/emself
- Star – star/star/stars/stars/starself
- Spivak – e/em/eir/eirs/emself
- Thon – thon/thon/thons/thons/thonself
- Avoid pronouns / use name as pronoun
- Questioning or unknown
- A pronoun set not listed here
The new sets on the list are star/star and thon/thon, which both made it into the top 11 in two age groups. Star/star made it into the list because of the 11-20 age groups. Thon/thon is one of the older creations in the English language (coined in 1858), and joins the list thanks to the 41-50 crowd.
Lost from the list next year will be:
- Ae – ae/aer/aer/aers/aerself – briefly the most popular write-in pronoun a couple of years ago, and added only last year. It was coined for a fictional alien in the 1920s.
- Ze/hir – ze/hir/hir/hirs/hirself – the first set of neopronouns for a nonbinary person that I ever encountered, almost 20 years ago. Pronouns containing ze stretch back to 1864.
As with the identity words, for pronouns I’ll use the median multiplier calculated from only adding pronouns to the checkbox list, not removing them.
Here’s this year’s pronoun checklist generator on the spreadsheet.
Q4: Family/relationship terms
Last year I embarked on a many-year mission to learn about preferences in terms that we use to describe our relationships to each other. That’s words like aunt/uncle, girlfriend/boyfriend, etc.
Each year I’ll ask two optional questions:
- The textbox question. This will ask about terms for a particular relationship for the first time, with several textboxes to type your answer. No checkboxes.
- The checkbox question. This will be a repeat of last year’s textbox question, with answers provided as checkboxes that are informed by last year’s answers. Textboxes also provided.
In this way we will gradually build up data about language for various social/family relationships in a reasonably fair way, without adding 10 new questions for people to get through. The theory is that year one gathers lots of information, and year two tidies it all up a bit.
The textbox question: sibling words
The survey asked, Imagine your sibling is introducing you to someone in English. Which word(s) would they ideally use to describe your family relationship to them? E.g. “This is [name], my _________.” This is the first time this question has been asked. Answers were in the form of five textboxes, and the question was optional. Participants were also given the following additional guidance:
- If you don’t have siblings, or if you do but they don’t speak English, answer hypothetically.
- It’s okay to enter non-English words that you would like your sibling(s) to use while speaking English.
Here’s our top 10:
- sibling: 67.2%
- brother: 21.2%
- sister: 20.5%
- sib: 3.3%
- bro: 1.3%
- sis: 1.0%
- older/younger sibling: 0.5%
- twin: 0.5%
- relative: 0.3%
- kin: 0.3%
Let’s see that as a bar graph:
In hindsight, I am not sure why I thought it would be okay to include the word sibling in the question, because I know from experience that this can skew the results. (I think I was concerned that “another child of your parents” might be too confusing?) However, I feel confident that sibling would have featured very highly in this list because it’s a very well established and frequently used gender-neutral word in English for other people who were born to your parents. I think the list of terms itself is sound, but the proportions are almost certainly unreliable because of my oversight.
Thankfully, as this system loosely intends, this can be fixed next year. The checkbox list will include sibling and be randomised to prevent bias, and the question wording will definitely not contain any concise nouns for the relationship it’s aiming to describe! Maybe something like:
Imagine another child of your parents is introducing you to someone in English. Which word(s) would they ideally use to describe your family relationship to them? E.g. “This is [name], my _________.”
- If your parents don’t have any other children, or if they do but they don’t speak English, answer hypothetically.
- It’s okay to enter non-English words that you would like other children of your parents to use while speaking English.
The checkbox question: parent words
The survey asked, What would you ideally like your children to call you when they are speaking to you in English? It then provided 10 parent-ish words, plus “my name”, “nickname based on my first name”, and “questioning or unknown”. These options were informed by the textbox responses to this question last year. The question was optional, participants could choose as many as they wanted, and there were five textboxes provided below for those whose words were not all on the checkbox list.
| Option | This year | Last year | Increase |
| [nickname based on my first name] | 30.0% | Impossible to count | |
| [my first name] | 23.9% | Impossible to count | |
| Questioning or unknown | 23.9% | Impossible to count | |
| Dad | 21.2% | 15.7% | 1.4x |
| Parent | 18.2% | 10.1% | 1.8x |
| Mom | 16.6% | 11.6% | 1.4x |
| Mama | 15.4% | 4.2% | 3.7x |
| Papa | 11.8% | 3.8% | 3.1x |
| Baba | 10.3% | 2.2% | 4.7x |
| Mum | 10.2% | 2.7% | 3.8x |
| Ren | 8.7% | 1.8% | 4.8x |
| Father | 7.5% | 3.1% | 2.4x |
| Mother | 6.2% | 1.9% | 3.3x |
Here’s the top 10 as a bar graph:
The main difference I’m noticing compared to last year’s textboxes is that names and nicknames are right at the top now, whereas last year my name only made fourth place. Without a checkbox option last year fewer people would think of it, but that’s the case for every other word in the top 10, so that doesn’t explain the shift. However, those who did think of it last year wouldn’t have had a uniform way to write it into the textboxes, which makes it much harder for me to count – so it’s possible that last year it was undercounted.
Another thing I’m noting is the exact context. The wording of the question invites people to give names they would like to be called by their children, but the familial title you’d like your children to use to describe your relationship to them in the third person (e.g. “I’ll need to go check with my _________ first”) is a different thing entirely. I won’t ask about that next year because I want another relationship to have a turn, but I will make a note of it for future years.
As I mentioned last year, there are some obvious cultural variations in these lists. If you’re investigating gender-neutral terms for mother/father and you want to prioritise regionally relevant terms, I recommend downloading the spreadsheet of results and cherry-picking the data for your country (or whichever specific country you have in mind).
The relationship words calculations are all on their own separate spreadsheet this year, which you can view here.
Meta
The last page of the survey asks participants for various bits of information, some of which help me to design a better survey and promote it effectively (age, feedback, referrer), and some of which make the data more useful for others (age, country).
- Age (grouped in 5-year increments)
- Country
- How you found out about the survey today
- Whether you’ve taken the survey before
Most of the graphs and summaries that I got out of them can be found on this year’s public participation sheet.
The top 5 countries represented by number of participants were:
- United States: 26,933 (55.4%)
- United Kingdom: 5,505
- Canada: 3,369
- Germany: 2,196
- Australia: 1,980
That’s the same countries in the top 5 as last year, but Germany and Aus have swapped places again. 67 countries got 10 or more responses, and any country with under 10 responses (of which there were 68) has had the country redacted to ensure participants’ privacy and safety.
Here it is as a bar graph:
You can read about how people found the survey here on the public participation sheet. There’s nothing much out of the ordinary, Tumblr was the main source at 41%, followed by Discord and the mailing list. I’m really glad the mailing list is still kicking, because it’s the best way to reach people of all age groups. Its ongoing kickingness is mostly thanks to diligent assistance from Andréa, my tech hero – please feel free to buy nice treats for her!
This year I finally decided to drop the Twitter account. The Mastodon account is bringing in 50% more people than Twitter, I started a Gender Census account on Bluesky, and I started an Instagram account on the recommendation of someone on Tumblr. Those three combined are more than making up for the lack of active Twitter account, with the bonus that they don’t penalise you if you post the word cisgender. (Having said that, I am very bad at Instagram, so maybe it’s best you don’t follow on that one, actually.)
This year people aged 31 and over were up by 6 percentage points (21%), which is great – I really want to show all kinds of people in the results, and age is a really tricky one on the internet. People who use the internet tend to be younger, and people who use social media younger still. Despite all my meta questions it’s still impossible to know why/how participants were older than usual this year, but I’m glad of it.
This all leads us to my never-ending problem: selection bias. The survey is 100% online, and spread entirely by word of mouth and social media shares. I put as much effort as I can every year into encouraging people to share it face-to-face, in social/support groups that they attend in person, on noticeboards, etc. This year 235 said they found the survey through a local support group, which isn’t nothing! The huge number of participants every year mitigates the selection bias in my heart, but in actual statistical ways it may not make much difference. It just means that readers have to bear in mind that these results may not reflect the feelings and preferences of people who don’t use the internet very much.
28% of participants had done the survey before and 60% hadn’t, which is about the same as last year:
Some of the questions this survey seeks to answer
- What should the third gender option on forms be called? – Nonbinary is the most commonly used, holding steady at around 60%. It’s far from universal, but there are no other comparably popular words in the top 10 that are unambiguous in meaning. I would recommend the third gender option be called nonbinary.
- Is there a standard neutral title yet? – No. Internationally, participants generally prefer to not have any title at all. Those designing forms collecting personal information must ensure that Mx is an option alongside Mr and Ms, but it is far more important (and increasingly important) that title fields in those forms are optional.
- Is there a standard gender-neutral way to respectfully address superiors and strangers (sir/ma’am) yet? Too soon to say for sure. There’s a lot of cultural variation. We only have two years of data, but avoiding sir/ma’am altogether is the most popular suggestion so far.
- Is there a pronoun that every nonbinary person is happy with? – No. They/them is a safe bet if you’re not sure what to use, being chosen by around 75% of participants since the first survey over a decade ago. But that leaves one quarter of us who don’t want to be called they, and 11% of us consistently don’t like to be called he, she or they, so it’s often good to check.
- Is there any consensus on a gender-exclusive nonbinary pronoun? – No. About 1 in 10 participants were happy with xe/xem/xyr/xyrs/xemself (singular verbs), but its popularity can fluctuate.
This year in review
Long. This report seems to get longer every year. Partly because I keep adding questions to the survey, and partly because as the project continues year on year there’s more data to look at for long term trends. Should I… try to stop it getting longer? Should I make a spreadsheet for tracking word count over time?
The new question on how to use people’s pronouns. It was pretty much unworkable, but that’s okay.
New checkbox selection method (again). The multiplier method is working so well that I’ve made it more thorough. Overall it’s letting the lists stay mostly the same year-to-year, while still making sure that people in different age groups are able to see themselves in the survey.
There’s a shop now! It has a zine about pronouns that I’m particularly proud of. Over 70 copies have already been bought.
Crowdfunding. As usual I haven’t done the maths yet, but I feel pretty confident that my costs were covered by Patreon pledges this year, and I am really grateful. There are a lot of significant costs involved with this project, and it is a pleasure to be able to pay Andréa for her work. You can visit the Gender Census Patreon project page here, and you can buy Andréa fancy things to say thank you here.
What I’ll do differently next year
- I’ll cut the identity textboxes down from 20 to 10.
- Unless I am struck by inspiration, I think I’ll have to drop the question about how people want their pronouns to be used.
Closing thoughts
I have been busy with another really big project this year, so it has been a valuable exercise in how to put my foot down and carve out time to write up this report. This year I’ve been reflecting on how much I’ve learned over the years as this project has stretched me, and how well those skills have served me in other areas of my life.
I am also really loving that we have enough data from enough years now that we can properly see linguistic trends shifting over time, which is why I started doing this annually to begin with! What an epic achievement, I’m proud of myself. Every year when I finish the report I am already excited for next year. 🤓
As always, thank you everyone for enabling my nerdery – participatorially, financially and emotionally. I really hope that this data is interesting or useful to many people. (If you use the stats in something not-self-published, please tell me so I can put it on Data in action!)
Footnotes and edits
✦ Including probably me. ^
Edits:
2024-09-19: Added note on “creature” meaning.
Support me!
Thank you for reading! If you find this report and this project to be valuable and would like to give something back, you could pledge to support the survey financially on Patreon, or increase your chances of taking part in future surveys by following on Tumblr, Facebook, Bluesky, Instagram, the Fediverse, or the mailing list. Alternatively, you could buy something from the new shop or take a look at my Amazon wishlist! 🍫
Links to files
- Unprocessed responses
- Processed responses – and I should warn you, this spreadsheet is LARGE (50 sheet-tabs) and may take a long time to sort itself out. Open it and then go and put the kettle on.
- All identities by all age groups spreadsheet
- Family/relationship words spreadsheet
- 2013-2024 trends
2024-09-18
email: hello@gendercensus.com