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the-xenogender-survey · 1 year ago

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Xenogender Usage Survey Results

At long last, the results of the Xeno survey have been published! Out of about 160 entries, about 120 were usable! Some of these results will be varying as certain questions were optional.

Results under the cut, because this is a long post and includes graphics. Enjoy!

Q1. Do you have a main/primary gender identity?

Q2. What is your main/primary gender identity (if yes)?

The top 5 most common 'main/primary' gender identities of respondents to this question were as follows: 5. Trans Man [4] 4. Genderfluid [4] 3. Agender [4] 2. Genderqueer [6] 1. Nonbinary [7]

See the full list of all 'main/primary' gender identities HERE.

Q3. What Xenogenders do you identify with/as?

As this was the BIG ONE, I encouraged folks to give their whole lists, no matter how long they may have been. The top 11 most common xenogender identities of respondents to this question were as follows:

11. Staticgender [x5] 10. Demongender [x5] 9. Chaosgender [x5] 8. Bungender [x5] 7. Xenogender (Standalone) [x6] 6. Glitchgender [x6] 5. Stargender [x7] 4. Pupgender [x7] 3. Autigender [x8] 2. Fictogender [x14] 1. Catgender [x19]

See the full list of all Xenogenders HERE. There are 1,346 genders on this list.

These results were particularly interesting to me, because despite the high amount of respondents, only 2 xenogenders went over 10 responses at all despite the massive overall number. Xenogenders are a very vast 'type' of gender with usually very personalized meanings.

Q4. Do you identify with any non-xenogender identities in addition to the xenogender identities you have?

Q5. What non-xenogender identities do you have (if yes)?

The top 11 most common non-xenogender identities of respondents to this question were as follows:

11. Gendervoid [6] 10. Demigirl [6] 9. Male [7] 8. Boyflux [7] 7. Bigender [7] 6. Transgender [11] 5. Genderqueer [13] 4. Genderfluid [15] 3. Agender [21] 2. Transmasc [25] 1. Nonbinary [33]

See the full list of non-xenogenders HERE. I did include neogenders and "cusp" genders in these results. Maybe I'll do a survey on neogenders in the future...

Q6. When talking about your gender(s) ONLINE, do you put more emphasis on your xenogender or non-xenogender identities?

Q7. When talking about your gender(s) OFFLINE/IRL, do you put more emphasis on your xenogender or non-xenogender identities?

Q8. When thinking about your gender(s) PRIVATELY/PERSONALLY, do you put more emphasis on your xenogender or non-xenogender identities?

The extreme variance in these charts is really interesting as well. I want to make this survey an annual thing, I'm curious to know if this will change at all over the years.

Q9. Do you use neopronouns? For the purposes of this survey, 'neopronouns' was defined as any pronoun that was not he/him, she/her, they/them, or a combo of them such as she/they.

Q10. What type of neopronouns do you use (if yes)?

Q11. Do you prefer if people refer to you with your neopronouns or your non-neopronoun pronouns?

Q12. Do you have any additional comments about your xenogenders or neopronouns?

These will be held to the end of the survey as it is the longest section. Q13. Are you Neurodivergent?

Q13. Do you feel as if your neurodivergence has an impact on your xenogender(s)?

Q14. What types of neurodivergency do you have?

The top 5 most common neurodivergencies of respondents to this question were as follows:

5. C-PTSD [39] 4. ADHD [58] 3. Depression [63] 2. Anxiety [66] 1. Autism [93]

See the full list of neurodivergencies HERE.

I do think these results support my hypothesis that there is a strong intersection of neurodivergency, as well as specifically with autism.

That is the end of the results section! Below are participant comments. I removed comments that clarified on their personal identities or comments directed specifically to me. I found a lot of these very insightful, so even though this section is long, I do recommend reading through them. Thank you to everyone who participated!

COMMENTS ABOUT XENOGENDERS:

>> I believe that there is a huge problem in Xenos where the coiners end up deleting their blogs or presence online so it makes it impossible almost to trace back the gender, as well as there not being a well documented enough place for people to access info on Xenos. The best I found that is specifically only for Xenos is a Wikidot but it doesn't have a lot in terms of some genders imo. There's a weird sort of sense where genders and pronouns become their own lost media, and it's sad. I wish we had a way to properly catalog them as best we could but it's nigh impossible as MOGAI and Xenos were intended to be made where anything could be a Xeno (which is good!) but in the wake, double-coining happens and we lose the ones we did coin in the end. Sorry to ramble oops

>>I think the fact that im otherkin influences my gender identity in major wayss

>>I love my xenos and my genders and i think id like to talk more about it irl.

>>i identify as [gender, removed for privacy] privately and do not share it anywhere outside of my close group of friends. i also only identify with it with my own definition, as every one i've seen online includes concepts (aligning with masculinity/femininity, including european concepts such as royalty, etc) that i either feel uncomfortable with or feel defeat the entire purpose of a xenogender to begin with.

>>We identify the body as sushigender for this reason: Sushi comes in many different styles and fillings, but it's still sushi. Therefore, we can present however we want and it's still us. (It's basically putting a xenogender to describe unlabeled/not caring too much about labels)

>>i wish people (both queer & not) were more accepting that gender expression can be silly and you can have fun with it! sometimes labels are goofy. sometimes pronouns are silly. it doesn't make them any less valid. end the sillyphobia!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

>>i barely attach my xenogenders to my actual gender and its mostly a representation of my entire identity , or some sort of fashion statement or something

>>Most of my xenogenders are private- I do not talk about them other than fairy and livia gender. This is because they are for me and not others, and most people do not need to know about them! :> however, though I will not admit this everywhere, my non-xenogender labels mostly only exist for other people. I am fairygender before I am trans, before I am bigender. I am liviagender before I am trans.

>>Sometimes I like to label, sometimes not, the xenogenders and other genders I identify with are all loose and fluid categories for me.

>>i only use xenogenders and neopronouns with other queer people.

>>i love love love the community this is so cool and i think everyone being able to express themselves is the most important thing in the world

>>I am satisfied with identifying with 'xenogender' as an umbrella term, rather than trying to find and list specific xenogenders I identify with. At least for now. Going to the effort of finding specific xenogenders has not been worth it to me so far.

>>Neurodivergence doesn't intersect with this as much as my alterhumanity does! I am a fairy and a pigeon. Neither has a concept of gender the way humans do. In an ideal world I would not have to fit myself into that system at all! Neurodivergence intersects because it intersects with everything. I am my brain. What it is is what I am. I can't run away from that.

COMMENTS ABOUT NEOPRONOUNS:

>>Most people don't use the neopronouns so it feels wrong to say I prefer them, sense they're never used

>>Honestly I only use my neos with close friends I'm sometimes public abt it but I'm too afraid of backlash sometimes

>>i sort of prefer folks to use my neopronouns purely as a result of most people NOT using them. if people actually used them equally, i would not feel that need to even things out.

>>We do notice people only using the first pronouns you list and ignoring the others (using exclusively she/her when the pronouns are she/they/xe/gem)

>>No one uses them and it makes me really dysphoria but I feel I can't enforce it because there so weird

COMMENTS ABOUT THE INTERSECTION OF NEURODIVERGENCY AND XENOGENDERS:

>>I do genuinely believe a lot of the xenogenders I have are related very specifically to my autism and how I perceive things around me, especially the sound / music related ones.

>>A lot of my overlap comes from perceiving the world around me differently, including my genders and the fluidity of my identity. I feel closer to sounds, concepts, objects, feelings, etc., than I do "typical" and "traditional" gender identities. I understand things more closely and easily in abstracts and metaphors when it comes to my own feelings, so things like "boy" and "girl" don't make much sense to me as a personal experience.

>>Autism affects that indirectly by being a major reason for my alterhumanity

>>My autism effects how I identify myself more than anything most of my xenogenders have to do with my special interests or stuff I feel like due to my autism

>>i have more genders than "usual" because of my multiplicity

>>The intersection most prominently comes from the autism. Being autistic has heavily impacted how I view my role in society and is influenced by a lot of that + my interests

>>autism is the Big one, because it makes me see and literally feel my gender differently to an allistic person. and OSDD-1b affects it only because it's a weird experience being transfem in an afab body, so my gender experience is quite different to singlets who are transfem

>>i think i likely would still experience xenogenders if i was neurotypical, but the fact that i am neurodivergent makes me experience them much more intensely

>>My dissociative disorder (OSDD) and autism majorly effect the way I view gender. It's almost entirely unimportant to me and I see it as more of a form of expression than anything and don't understand why so much stock is put into gender.

>>considering how alienated and disconnected i am from my identity and everyone else, i feel that using xenogenders that feel unclear or 'strange' gives me a sense of identity. i enjoy coming off as strange or offputting to others and like using queerness and nonconformity to express that.

>>my nonhumanity and my aroaceness are a lot more relevant to my gender than my neurodivergencies are.

>>I am not sure if my neurodivergence affects my xenogenders or not, but I know that it affects my overall gender identity, and that is why I label myself as interestfluid.

>>my concept of gender is just weird

>>It’s definitely interesting how a neurodivergency can allow someone to view gender in so many different ways. As an Autistic person, I genuinely do not understand the binary and construct that society has laid out. This in turn affects how I try to conceptualize something that I honestly don’t think *can* be conceptualized. It’s so unique to each person

>>Our autism causes us to see gender from a different perspective so to say. And being a system, other alters also have other perspectives and preferences and identities

#Xenogenders #Xenogender #Neurodivergence #Neurodiversity #Neurodivergent #Survey Research #Survey Results

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superlinguo · 10 months ago

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Superlinguo 2023 in review

I spent 2023 on leave to hang out with a new tiny human. I still found time for some linguistics, including regular Lingthusiasm episodes and even some intermittent blogging. I also got to reuse all my linguist pregnancy announcement jokes.

Lingthusiasm

Lingthusiasm turned 7 this year! We celebrated with a dozen main episodes as well as our monthly bonus episodes for patrons. We had some help to get through the year while I was on leave with interviews with linguists from around the world, including Lingthusiasm team members Martha Tsutsi-Billins and Sara Dopierela.

We released our new Etymology isn't Destiny merch, which is available alongside merch for all kinds of linguists and language fans.

Main episodes

Where language names come from and why they change (transcript)

How kids learn language in Singapore - Interview with Woon Fei Ting (transcript)

Bringing stories to life in Auslan - Interview with Gabrielle Hodge (transcript)

Tone and Intonation? Tone and Intonation! (transcript)

Word Magic (transcript)

The verbs had been being helped by auxiliaries (transcript)

Frogs, pears, and more staples from linguistics example sentences (transcript)

How kids learn Q’anjob’al and other Mayan languages - Interview with Pedro Mateo Pedro (transcript)

Look, it’s deixis, a word for linguistic pointing! (transcript)

Ergativity delights us (transcript)

Revival, reggaeton, and rejecting unicorns - Basque interview with Itxaso Rodríguez-Ordóñez (transcript)

If I were an irrealis episode (transcript)

Bonus episodes

Parrots, art and what even is a word - deleted scenes from Kat Gupta, Lucy Maddox and Randall Munroe interviews

Singapore, New Zealand, and a favourite linguistics paper - 2023 Year Ahead Chat

When books speculate on the future of English

Neopronouns, gender-neutral vocab, and why linguistic gender even exists - Liveshow Q&A with Kirby Conrod

2022 Survey Results - kiki/bouba, synesthesia fomo, and pluralizing emoji

Linguistic jobs beyond academia

LingthusiASMR - The Harvard Sentences

How we make Lingthusiasm transcripts - Interview with Sarah Dopierala

Field Notes on linguistic fieldwork - Interview with Martha Tsutsui Billins

Postcards from linguistics summer camp

Linguistic Advice - Challenging grammar snobs, finding linguistic community, accents in singing, and more

Frak, smeg, and more swearing in fiction - Ex Urbe Ad Astra interview with Jo Walton and Ada Palmer

LingComm: 2023 conference

The 2023 LingComm conference happened in February, and was once again in the LingComm conference space in Gather Town. I enjoyed being on the planning committee that put together an amazing event that built on the inaugural conference in 2021. Stay tuned for 2024 lingcomm updates!

Top Superlinguo posts in 2022

This year was a chance to reflect on the decade since I graduated, and to articulate the important role my main supervisor had in shaping my career.

After wrapping up the linguistics jobs interview series last year, this year was a chance to share some aggregated resources from 8 years and 80 interviews.

I also got to read a couple of great linguistics books for kids, keep up to date with linguistics podcasts, share some of my favourite linguistics books and check in on some things happening online.

General posts and reviews

10 years of a PhD

Barb Kelly

Gender Variations for Person in Suit Levitating Emoji - Emoji Proposal

Linguistics and Language Podcasts (2023 update)

Language Books for Kids: Highly Irregular, Arika Okrent & Sean O'Neill

Linguistics books for kids: Once Upon a Word - a Word-origin Dictionary, Jess Zafarris

Linguistics Jobs resources

Linguistics Jobs Interviews - directory of posts and resources

Linguistics Jobs resource set

Superlinguo Linguist Job Interviews full list

Linguistics education and its application in the workplace: An analysis of interviews with linguistics graduates (new publication in Language)

Information and advice

hapax legomenon and automated email replies

Lingthusiasm guide to pop linguistics books

Hello Grambank! A new typological database of 2,467 language varieties

What we can accomplish in 30 years of lingcomm: Opening keynote of #LingComm23

Australian Linguistic Society’s Accredited Linguist program

Academic articles in 2023

Although I was on leave, things that I was working on earlier made it through to publication. I like that there was one paper on lingcomm, one on gesture (including emoji!) and one on the linguistics job interviews, it feels like a nice mix of some of my current interests. Just a pity there wasn't a Tibeto-Burman paper in there!

Gawne, L. & A. Cabraal. 2023. Linguistics education and its application in the workplace: an analysis of interviews with linguistics graduates. Language, 99(1), e35-e57. [doi][Superlinguo post]

Freestone, P., J. Kruk & L. Gawne. forthcoming. From Star Trek to The Hunger Games: emblem gestures in science fiction and their uptake in popular culture. Linguistic Vanguard, 9(3), 257-266. [doi][Superlinguo post]

Gawne, L., & McCulloch, G. (2023). ‘Communicating about linguistics using lingcomm-driven evidence: Lingthusiasm podcast as a case study’, Language and Linguistics Compass, 17/5: e12499. DOI: 10.1111/lnc3.12499 [doi][Superlinguo post]

The year ahead

I'll be back to work full time. I've found the low-key level of blogging I managed this year to be sustainable, so expect it to be business-as-usual here. Lingthusiasm will also continue with monthly main and bonus episodes, thanks to the patrons who support the show and ensure we have a team that can keep everything rolling while begin to take on more administrative responsibilities in my job.

I'm looking forward to sharing some things that are in the final stages of peer-review and copy editing, and I'm excited to be spinning up some new projects.

Browsing old Superlinguo content?

I have a welcome page on the blog that points you to aggregate posts, and series of posts I've done over the years, as well as themed collections of posts that have appeared on the blog in the last twelve years.

Previous years

Superlinguo 2022 in review

Superlinguo 2021 in review

Superlinguo 2020 in review

Superlinguo 2020 (2019 in review)

Superlinguo 2019 (2018 in review)

Superlinguo 2018 (2017 in review)

Superlinguo 2017 (2016 in review)

Superlinguo 2015 highlights

#linguistics #language #superlinguo #2023 #review

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neopronounsmybelovaed · 3 years ago

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Neopronouns- Full List

All of the neopronouns found on the survey. All of them.

Part one under the cut

___/___

:)/:)

:]/:]s

:0/:0s

:3/:3/:3s/:3s/:3self

‼️/‼️self

!?/!?self

?!/?!s

?/?

?/??

..°̸͙͊͘ /..°̸͙͊͘

.doc/.doc/.docs/.docs/.docself

.exe/.exe

₍ᐢ.ˬ.⑅ᐢ₎/₍ᐢ.ˬ.⑅ᐢ₎

[ ]/[ ]

[REDACTED]/[REDACTED]s

**/**

*/*s

*e/h*

̴̡͈̜̙̜̫͉͈̲̺̦͕̦̳̒͌͐̓̉̆̀͆̓͘/̴̼̹͑ ̸̛̝̩̫̫̲̱̎͌̇̑̇̑̀̕̕/̵̤̺̣̝͙̱̙͋̋̍̈́̓̽ ̶̛͇̙̺͔̬͓̼͗́̎̆͛͌͝��̭̞̗͖̙ ̶̨̬̙̤͍̮̗̙̟͉̊͑ͅ/̴̧̧̲̟̏̎͒̍̕ ̷̲̰͔͓͉̜͖̳̝̼̥̅̍ ̸̨̲̈́̎/̴̨̳͎̹̘͇̪͍̤͓͚̳͔̥̐̅̍̾̐̎̓̚͠͠ ̴͚͕̼͉̹̬͓̭̤̯̪͚͔̺̈́̈́̐̔̎̔̽͂́̕self

&/&

#/#

%/%

༄/༄

>:3/>:3

~/~

███/███

☁️/ ☁️

☎️/☎️

☔/☔

☕/☕

☢️/☢️

♂️/♂️

♠/♠

⚙️/⚙️s

⚠️/⚠️

⚡/⚡

⚫️/⚫️

⚰/⚰

⛄️/⛄️/⛄️s/⛄️s/⛄️self

⛓️/⛓️

⛧/⛧

⛽/⛽

✒️/✒️

✨/✨

❄/❄

❔/❔s

❤/❤

❤💛💙/❤💛💙

⬛/⬛/⬛s/⬛s/⬛self

⭐️/⭐️

⭕/⭕/⭕s/⭕s/⭕self

🃏/ 🃏

🌀/🌀s

🌀/him

🌃/🌃

🌆/🌆

🌈/🌈

🌌/🌌

🌎/🌎s

🌑/🌑

🌕/🌔

🌕/🌖

🌙/🌙

🌡️/🌡️

🌥/🌥

🌧/🌧

🌩️/🌩️

🌫️/🌫️

🌱/🌱s

🌲/🌲’s

🌳/🌳s

🌵/🌵

🌶/🌶

🌷/🌷

🌸/🌸

🌹/🌹

🌼/🌼

🌿/🌿s

🍂/🍂’s

🍄/🍄

🍉/🍉/🍉s/🍉s/🍉self

🍒/🍒

🍓/🍓

🍖/🍖s

🍥/🍥

🍩/🍩

🍪/🍪

🍬/🍬

🍭/ 🍭

🍳/🍳

🍵/🍵

🍼/🍼

🎀/ 🎀

🎃/🎃

🎉/🎉s

🎒/🎒

🎞️/🎞

🎠/ 🎠

🎡/🎡

🎤/🎤

🎮/🎮

🎰/🎰s

🎲/🎲

🎵/🎵

🎶/🎶

🎼/🎼

🏹/🏹

🐀/🐀

🐁/🐁

🐇/🐇

🐍/🐍

🐏/🐏

🐐/🐐

🐑/🐑

🐑/💙

🐖/🐖

🐛/🐛

🐜/🐜

🐢/🐢

🐥/🐥

🐦/🐦s

🐧/🐧

🐨/🐨

🐭/🐭

🐰/🐰

🐱/🐱

🐶/🐶s

🐷/🐷s

🐸/🐸

🐺/🐺

🐾/🐾

👁/👁

👁️‍🗨️/👁️‍🗨️s

👑/👑

👹/👹s

👻/👻

👽/👽

👾/ 👾

💀/💀

💉/💉

💋/💋s

💌/ 💌

💎/💎

💕/💕

💖/💖

💗/💗

💙/💙

💙/💜

💚/💚

💛/💛s

💠/💠self

💡/💡

💤/💤

💥/💥

💨/💨’s

💫/💫

💽/💽

💾/💾

💿/💿

📄/📄s

📑/📑

📚/📚

📜/📜

📰/📰

🔇/🔇

🔋/🔋

🔌/🔌

🔥/🔥

🔪/🔪

🔮/🔮

🕊️/🕊️

🕯️/🕯️

🕷️/🕷️

🕸/🕸

🕹/🕹

🖊️/🖊️

🖍/🖍

🖤/🖤

🗝/🗝

🗞/🗞

🤡/🤡

🥀/🥀

🥁/🥁s

🥚/🥚

🥝/🥝

🥩/🥩

🥪/🥪

🥫/🥫

🦇/🦇

🦈/ 🦈's

🦊/🦊

🦋/🦋

🦔/🦔

🦕/🦕

🦝/🦝

🦠/🦠

🦴/🦴

🦷/🦷

🧀/🧀s

🧟‍♂️/🧟‍♂️

🧡/🧡

🧪/🧪

🧱/🧱

🧸/🧸

🧼/🧼

🩹/ 🩹

🪐/🪐

🪱/🪱

🪲/🪲

🪵/🪵’s

🪶/🪶

🫀/🫀

😈/😈

😴/😴

🙂/🙂s

🚂/🚂

🛸/🛸

2b/2b

3/3self

3/3z

3√2/3√2

3rr0r/3rr0r

4/4s

404/404s

5/5self

5/5z

7/7s

9/9self

a/ace

a/aros

abnu/abnure

abstra/abstract

abyss/abysmal

abyss/abyss

ace/ace

ae/ae

ae/aem

ae/aer

ae/aether

ael/ael

aeon/aeon

aerixa/aerixae

aethr/aethrs

af/afself

agri/agrius

ai/ai

ai/aim

ai/ain

al/ala

al/allium

ala/alum

alien/alien

all/alls

alli/allium

alt/alter

an/anself

Andromeda/Andromeda's

ang/angel

angel/angel

anny/andro

another/anotherself

ant/ant

ap/aps

aqua/aquas

ar/ars

ar/arso

arcade/arcadeself

arcade/arcem

arcane/arcane

arch/archer

aro/aroself

arson/arsons

art/artself

ast/aster

astro/astroself

ato/atom

au/aur

au/auti

autumn/autumnal

ax/axo

axo/lotl

az/az

azu/azur

ba/bat

baa/baa

bam/bang

ban/ana

ban/banner

bard/bards

bark/bark

bast/bastard

bat/bat

be/berry

be/rym

bea/bea

bea/bead

bea/beam

bead/bead

bean/beans

bear/bears

beau/beaus

beauty/beautys

bee/bee

bee/bem

bell/bell

bendy/bendy

ber/berry

berr/berry

berry/berries

bet/bets

bey/bem

bid/bids

bim/bim

bir/birds

bit/bit

bit/bite

bite/bite

bl/blue

bla/blade

black/black

blade/blades

blank/blank

blast/blast

blip/blip

blo/bloom

bloo/blood

bloo/blook

blood/bloods

blook/blooky

bloom/bloom

bloop/blooper

blrrp/blrrrps

blu/blu

blu/blue

blu/blur

blue/blue

blur/blurs

blush/blushs

bo/boar

bo/bole

bo/bolt

bo/bon

bo/bone

bo/bos

bog/bog

bomb/bomb

bon/bone

bon/bonk

bon/bons

bone/boneself

bonk/bonk

boo/boo

book/book

boom/boom

boop/boops

bop/beep

bork/bark

bot/bots

boun/bounce

boy/boy

brack/bracken

brain/brains

bread/breadself

breeze/breeze

bri/bright

bright/brightself

bro/bros

bu/buck

bu/buzz

bub/bubble

bubble/bubble

buck/buck

bug/bug

bumble/bee

bun/bun

bun/bunny

bun/bunz

bunnydog/bunnydog

burn/burns

buzz/buzz

byte/byte

ca/can

ca/cand

ca/care

ca/catta

ca/nine

cae/caer

cake/cakeself

calm/calms

cand/candied

candel/candel

candi/candiself

candle/candles

candy/candie

candy/candy

cap/tain

card/cards

care/cares

cat/catboy

cat/cats

cat/nip

catboy/catboy

catdog/catdog

caw/caw

caw/crow

ce/cedar

ce/cem

ce/cer

ce/cir

ce/lai

cel/celes

cel/celest

cel/cem

cha/chase

chae/chane

chai/chaim

chai/chain

champ/ion

chao/chaos

chaos/chaos

chaotic/chaoticself

chat/chatter

chem/chemic

cher/chers

cherry/cherries

chet/chets

chev/chevalier

chew/chew

chi/chime

chi/chir

chi/chirp

chir/chirp

chirp/chirps

cho/choco

cho/chos

chocolate/chocolate

chomp/chomps

chor/chorus

chord/chord

chron/chrono

chrrp/chrrps

ci/ciph

ci/cipher

ci/circ

cie/cier

cin/cinna

cinna/cinnas

cit/rys

citru/citrus

cla/claw

clemen/tine

cli/click

click/clicks

clink/clink

clo/clos

clo/cloud

clo/clove

clock/clocks

clot/clots

cloud/cloud

clow/cloud

clow/clow

clown/clown

co/cem

co/coal

co/cobble

co/cocoa

co/code

co/coin

co/con

co/copy

co/cos

co/cotton

co/ney

cocoa/cocoa

coffee/coffeeself

cog/cog

coi/coin

coin/coin

cola/colas

color/colors

com/comfort

com/comi

com/rade

comb/comb

comfy/comfys

comrade/comrade

con/cons

con/contract

coo/cookie

coo/coos

cookie/cookies

🆒/🆒

cor/cord

cor/corpse

cor/corv

cor/corvid

core/core

corp/corpse

cos/cos

cotton/candy

crackle/crackle

craft/craft

cre/creature

cre/creme

cream/puff

creature/creatureself

crick/et

cringe/cringeself

cro/crow

cro/crown

crow/crown

crow/crows

crown/crown

cru/crumb

crum/crumb

crun/crunch

cry/cryp

cry/crys

cryp/cryps

cryp/crypt

crypt/cryptic

crypt/cryptid

crypt/crypts

cryptid/cryptids

cryst/crystal

cub/cub

cube/cubes

cup/cake

cup/cups

curse/curseself

cut/cuts

cute/cute

cy/cyb

cy/kes

cyc/cyclo

da/damned

da/dan

dae/daem

dae/daer

dae/dark

dae/death

dahlia/dahliaself

dai/daim

dai/daisy

damp/damp

dar/dark

dar/darling

dark/darker

dark/darks

data/data

dawn/dawns

dawn/dusk

day/enu

daze/daze

de/cay

de/decay

de/dem

de/demon

de/dew

de/dim

de/mon

dea/dead

dea/death

dead/dead

death/deaths

decay/decay

dei/deim

dei/deity

deity/deity

dem/demise

dem/demon

demon/demons

den/den

deox/deox

des/despair

des/pai

detect/detect

dex/dexself

dey/dem

di/devi

di/dice

di/dip

di/div

dia/dem

diamond/diamonds

did/div

die/dies

dino/dino

dino/saur

dip/dipp

dir/dirt

dirt/dirt

disc/disc

disc/discord

discord/discords

div/divs

divine/divineself

do/doe

doggy/doggy

dol/doldrum

doll/doll

doom/day

dora/doras

dorm/dormi

dot/dot

dra/drag

drae/draer

dragon/dragons

dre/dream

dread/dreadself

dream/dreams

dream/dreamy

dree/drem

drop/drip

drowse/drowse

dsic/discord

du/dusk

dude/dudeself

duke/dukes

dus/dust

dusk/dusk

dust/dusts

e/em

e/er

e/es

e/fe

e/im

e/ver

earth/earths

ec/echo

ech/echo

echo/echos

ee/eel

ee/vees

eev/eevs

eevee/eevees

egg/eggy

el/eld

el/elk

el/els

el/stel

eld/eld

elle/stelle

elm/elm

em/er

ember/ember

emo/emos

empty/empty

en/by

en/en

en/end

en/enter

en/entity

end/ended

end/ender

end/ends

ender/enders

endo/endos

eni/enis

entity/entity

eon/eon

er/ero

eri/eri

error/error

eso/esos

esp/espi

et/et

etc/etcs

etern/eternity

eth/eth

ether/ethereal

eu/euch

ev/ever

ev/evil

eve/evil

ex/extra

exe/exe

ey/em

ey/eye

eye strain/eye strain

eye/eyes

eyn/eyn

f/fself

fade/fades

fae/fae

fae/faem

fae/faer

fae/fake

fae/fem

faery/faery

fai/fairy

fairy/fairy

fall/fallen

fang/fang

fang/fangz

far/farce

fate/fates

faun/faun

fawn/fawn

fay/fay

fe/fel

feath/feather

feather/feathers

fee/fi

fel/feli

fel/fels

fen/fen

fer/fern

feral/feral

fern/fern

ferret/ferrets

fey/fern

fey/feyr

fi/fir

fi/fire

fic/fiction

fie/fire

fin/fins

fir/fir

fish/fish

five/fiveself

fiz/fiz

fizz/fizz

fizz/fizzy

fl/flu

fla/flame

fla/flare

flame/flame

flar/flareon

flare/flares

fle/flesh

fleur/fleur

fleur/fleurn

fli/flight

fli/flit

flick/flicker

flo/float

flo/flor

flo/flower

floccinaucinihilipilification/floccinaucinihilipilification

flow/flows

flower/flowers

fluff/fluff

fo/ster

fog/fog

fool/fools

for/forest

four/fours

fox/fox

fra/frost

fre/fir

freak/freak

fri/fri

friend/friends

fro/frog

fro/fronds

frog/frogself

fru/fruit

fruit/fruit

fu/fuzz

fuck/fucker

fuck/you

fun/fun

funeral/funeral

fungi/fungiself

fur/furs

fuz/fuzz

fuzz/fuzz

fy/fyre

fyr/fyr

g/gself

ga/gal

ga/game

ga/me

gala/galaxy

galaxy/galax

gall/gallant

gam/gamble

game/gameboy

game/games

gas/gases

gaso/gasoline

ge/geist

ge/gem

gear/gear

gem/gem

gender/gender

germ/germs

ghast/ghastself

#this is literally so long i had to split it into two posts #tumblr wouldn't let me post it otherwise #pronoun list #neopronoun list #neopronoun survey results

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neopronounsmybelovaed · 3 years ago

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You phrased that really well, it's something that's been floating around in my head for a while but I never quite knew how to explain it. I've been telling my friends "I like the word queer! It means weird, and you know what? I am weird! And I like being weird!"

Also, a lot of the idea of normalcy is based on neurotypical societal, well, norms. So I checked something on the survey data.

Out of all the 252 people who used queer as a label for either their orientation or their gender, five were neurotypical. That's not even 2 percent (1.984%). So I think "q is a slur" has an element of ableism invovled.

Hot take: One of the things at the root of the "q is a slur" discourse is that exclusionists base their activism on expanding the definition of "normal", while inclusionist activism is about destroying the concept of "normal".

I mean of course everyone knows the issue is not queer being a reclaimed slur, gay and lesbian are reclaimed slurs too and no one has any problem with that. Exclusionists single out the word queer because of what it stands for. Because it is ambiguous and inclusive, yes, but also because it says "not normal", it embraces deviating, openly defying normativity, being different.

I've seen "q is a slur" people say that they are specifically against that word because they don't want to be seen as strange, because their fight is about being accepted as "normal". I've had an aphobe tell me people saying "demisexual means normal" is a privilege because actually oppressed people want to be seen as "normal" and me wanting my identity to be acknowledged is oppression fantasy. Apparently to them normalcy is so important that having your identity erased is a good thing.

Queer people are oppressed because the world doesn't see us as normal, and to exclusionists the solution is expanding the box of normalcy to fit themselves into it. To them that's what Really Oppressed people should do, and those of us who embrace queerness are privileged because we want to call ourselves "freaks". To them any identity that is ambiguous or out of the ordinary, be it microlabels, neopronouns, xenogenders, aspec labels, m-spec labels or anything else is too weird and "makes the community look bad", because their activism hinges on allocishet acceptance and anything that doesn't fit in a box and cannot be defined easily is not oppressed enough for their taste.

Tl;dr: the "q is a slur" discourse and obsession with normal is just licking the boots of conformity and exclusionist activism is about fitting into the "normal" of the cisheteronormative world, while inclusionist activism entails defying the oppressive construct of "normal". Thank you for coming to my Ted talk.

Exclusionists dni, as always :D

#queer is not a slur #queer #queer pride #neopronoun survey results #you put it really well op thank you #queue/queer

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gay-otlc · 3 years ago

Text

Tumblr KOTLC Fandom- Pronoun Demographics

From the survey @an-ungraeceful-swan and I made, here are the results of the question asking "What pronouns do you use?" Participants each wrote in an answer. There were 94 responses.

@tiergan-andrin-alenefar

Hypothesis: There will be more xe/xem users than he/him users

(note: 19 people used all pronouns, so 19 was added to the number of pronouns explicitly specified for each pronoun set)

(another note: all decimals are rounded to the tenths place)

In order of most commonly used pronouns, we have

they/them, at 61 total users (~64.9%)

she/her, at 58 total users (~61.7%)

he/him, at 37 total users (~39.4%)

xe/xem, at 31 total users (~33.0%)

ae/aer, at 30 total users (~31.9%)

fae/faer, at 27 total users (~28.7%)

it/its, at 26 total users (~27.7%)

ey/em, at 21 total users (~22.3%)

ze/hir, at 21 total users (~22.3%)

voi/void, at 20 total users (~21.3%)

cat/cats, at 20 total users (~21.3%)

sea/sear, at 20 total users (~21.3%)

lea/leaf, at 20 total users (~21.3%)

ve/ver, at 20 total users (~21.3%)

disc/discs, at 20 total users (~21.3%)

sil/ver, at 20 total users (~21.3%)

sol/sols, at 20 total users (~21.3%)

star/stars, at 20 total users (~21.3%)

hx/hxm, at 20 total users (~21.3%)

ar/son, at 20 total users (~21.3%)

cy/cyr, at 20 total users (~21.3%)

The data does not support the hypothesis. However, the data does not automatically reject the hypothesis.

Since he/him and xe/xem are the only proportions necessary for this hypothesis, confidence intervals have only been constructed for the two of them. I am 95% confident that the true proportion of he/him users in the KOTLC tumblr fandom is between 29.3% and 49.4%. I am also 95% confident that the true proportion of xe/xem users in the KOTLC tumblr fandom is between 23.3% and 42.7%.

Because of the overlap, there is no significant evidence that either set of pronouns has more users within the KOTLC tumblr fandom.

#kotlc survey #math gay wisdom #xe/xem #neopronouns of the lost cities #shoutout to my 29 new ae/aer best friends #love the number of neopronouns hir yall are amazing #also the way they/them is the highest like... this fandom sure can cisn't #anyway #this was a lot of fun thanks to everyone who filled it out #not me formatting this tumblr post as though my old stats teacher is gonna see it #if my stats teacher is following me on tumblr uhhhh hi but also wtf #kotlc survey results

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gendercensus · 6 years ago

Text

Gender Census 2019 - The Full Report (Worldwide)

This is a long post! You can see a summary of the big three questions here.

Hi and welcome to this year’s worldwide report based on the 11,242 responses to the Gender Census, which ran from 25th February until 30th March. It was mostly shared on Tumblr and Twitter, with some Reddit and Facebook and no doubt some one-to-one link-sharing too.

You can see the spreadsheet of results in full here, which might be helpful if you need to see graphs or figures in more detail. For the charts and graphs of statistics over time, the summary spreadsheet can be found here.

Q1. IDENTITY WORDS

As in previous years, I asked: Which of the following best describe(s) in English how you think of yourself?

Here’s the top 5:

nonbinary - 66.6% (up 6%)

queer - 43.0% (up 40.1%)

trans - 36.6% (up 1.8%)

enby - 31.7% (up 7.2%)

transgender - 30.4% (up 2.5%)

I put queer in bold because it’s new to the list, and the way it’s rocketed to second place is very unusual... and a little suspicious.

The wording of the identity question carefully avoids mentioning gender so that people without genders feel comfortable answering (or not answering), but it’s not really meant to include sexualities. The exception is sexualities that are part of someone’s gender identity, like this comment that someone wrote into the identity checkbox: “femme lesbian (sometimes i feel like lesbian *is* my gender)”

So anyway, last year queer got 2.9% (over the 1% threshold), and I personally know people who feel that their gender is queer, so I added it to the list. Usually when terms are added as checkbox options it might multiply their popularity by about four, but 43% is way too high to be explained by that. Queer is usually used to describe sexuality, so I think perhaps people who identify as queer in terms of their sexuality might have been selecting it too. I’m considering changing it slightly, to something like “queer (as gender identity)” to clarify it for next year. It’s possible that we won’t know if this percentage is due to bad survey design for a year or two.

(Edit: Some feedback on queer and my response to the feedback can be found here.)

Along those lines, several terms were added to the checkbox options this year because they were typed in by over 1% of participants last year:

queer

genderless

demiboy

demigirl

gender non-conforming

There are now 28 terms in the identity checkbox list, and as usual there were people expressing gratitude for the abundance of checkbox options in the identity question. However, there has also been an increase in people entering words into the textboxes that are already in the checkbox list. That means that people are missing or are not able to find the identity words they connect with more than last year, and it doesn’t help that the list is randomised to reduce primacy and recency bias.

Right now I add words to the checkbox list if they reach 1%, and this year for the first time I am considering adding another system for removing words that are not used as much. You can read a blog post I wrote about that here. I concluded based on the results of the 2017 survey (which asked for participants’ ages) that some words that seem to be used less overall are used more often by participants over 30, and since participants over 30 are underrepresented in online surveys generally I will be keeping any word that they enter over 3% of the time even if the word isn’t used as much overall.

Relatedly, I didn’t ask for ages in the survey this year, but I will be collecting information about age in future surveys to make sure that I don’t remove words and accidentally alienate underrepresented age groups. (The age question will be optional and will give age ranges rather than asking for an exact age, so hopefully that won’t make people feel too uncomfortable.)

This year someone complained for the first time that I was excluding words from other languages because I specify “in English” in the question, and if you know me from previous surveys you know that’s the opposite of my intention! Every word entered is counted, and I’m very aware that people use words from other languages while speaking English. So I’m considering rewording the question, but I welcome feedback on this since I’ve never had anyone complain about this issue before and plenty of people already enter non-English words.

And here’s this year’s top 10 words and their popularity over time:

Those two lines shooting up from 2018 to 2019 are two of the words newly added this year: queer and gender non-conforming. That green line starting near the bottom in 2016 and steadily increasing over time is more like what I’d usually expect - that’s enby, which is now up to #4 on the list.

There are no new identity words to add next year; the closest to 1% was butch with 0.7%. However, since I intend to collect information about age and since people often type, for example, “girl but not woman, even though I am not a minor”, I will be splitting girl, woman, man and boy into separate checkboxes next year.

2,021 unique identity words/terms were typed into the “other” textbox, including 413 that were entered more than once. The average number of type-ins for people who actually typed words in was 1.8, and the average words per person overall was 5. Most entered 4 words:

Q2: THE TITLE QUESTION

I asked, Supposing all title fields on forms were optional and write-your-own, what would you want yours to be in English? I also clarified that participants should be currently entitled to use it, so they should have a doctorate if they choose Dr, etc.

There were 5 specific titles to choose from, plus a few options like “I choose on the day” and “a non-gendered professional or academic title”. Participants could choose only one, with the goal of finding out what, when pressed, people enter on official records forms and ID.

Here’s our top 5:

No title at all - 33.0% (up 0.6%)

Mx - 31.3% (down 1.3%)

Mr - 8.7% (up 0.2%)

Non-gendered prof/acad. - 5.5% (up 0.1%)

Ms - 4.7% (down 1.0%)

Here’s how that looks compared with previous years:

Mx and no title switched places again for the fifth year in a row! And this year I made a similar graph but without Mx and no title. They always get way more than everything else, and it makes it really hard to see what’s going on in the lower half of the graph!

That rollercoaster of a red line is because in 2018 I specified that “non-gendered professional/academic title” should be one that the participant should be entitled to use, which caused that significant drop.

The most popular five “other” textbox titles were:

M - 28 (0.2%)

Comrade - 17

Sir - 10

Mrs - 9

Ser - 7

As with last year, I invited people who chose “a standard title that is used only by people other than men and women” (2.5% of participants) to optionally suggest titles that they’d heard of. The goal is to find a popular title that is considered exclusive to nonbinary genders the way Mr is generally considered exclusive to men and Ms is to women.

243 people checked the “standard exclusive nonbinary” title option, and here’s everything entered more than once:

Mx - 16

M - 4

Xr - 2

Mrs - 2

Mx is generally considered gender-inclusive by people who are familiar with it, especially if their title is Mx, but it’s high on this list because Mx is very well-known generally. M in French is masculine, but in English it’s not gendered and I assume it’s pronounced “em”? (That seems to be what people have said in the notes, but please do tell me if I’m wrong!) It was also the most entered title in the “other” textbox. Xr is new to me, I’m not sure how it’s pronounced.

Q3: PRONOUNS

The fourth question was actually a complex set of questions retained from last year, which started with 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? This was accompanied by a list of pre-written checkbox options. It included “a pronoun set not listed here”. and if you chose that it took you to a separate set of questions that let you enter up to five pronoun sets in detail.

As usual, everything that was a pre-written checkbox option got over 1%.

Here’s the top 5:

Singular they - they/them/their/theirs/themself - 79.5% (up 2.1%)

He - he/him/his/his/himself - 30.8% (down 0.4%)

She - she/her/her/hers/herself - 29.0% (down 1.9%)

None/avoid pronouns - 10.3% (up 0.2%)

Xe - xe/xem/xyr/xyrs/xemself - 7.2% (down 0.2%)

Here’s how that looks over time:

Because singular they, he and she always do better than everything else, let’s look at that chart without them. Every other specific pronoun set got under 8%.

Here’s the top 5 textbox neopronouns, none of which got over 1%:

ne/nem/nemself (singular verbs) - 27 (0.2%)

ve/ver/verself (singular verbs) - 24

ey/em/emself (singular verbs) - 23

ae/aer/aerself (singular verbs) - 22

thon/thon/thonself (singular verbs) - 18

(I’m going by the subject, object and reflexive, because that seems like the best way to collect similar sets together - eyeballing it, the most variations occur in the possessives.)

Half of participants don’t like he or she, and 9% like neither he, she nor they. 695 unique sets of neopronouns were entered by 574 people, of which 84 were entered more than once. The average number of pronouns entered was 2.2, and most people (39%) were happy with one set.

Overall it looks like there are no neopronouns really gaining in popularity, and even the checkbox neopronouns are being used less since 2015.

THE QUESTIONS I ASK

What should the third gender option on forms be called? - Still no consensus, but nonbinary is at 2 in 3 people and it does seem to be gradually climbing.

Is there a standard neutral title yet? - Not yet. Mx is still consistently far more popular than all other titles, but just as many nonbinary people want no title at all. It’s really important that activists campaigning for greater acceptance of gender diversity remember to fight for titles to be optional, too.

Is there a pronoun that every nonbinary person is happy with? - No. The closest we have to a standard is singular they, and it’s important for journalists and anyone else with a style guide to allow it. It’s levelled out at about 1 in 5 not being into singular they, and 9% of us don’t like he, she or they pronouns.

Are any of the neopronouns gaining ground in a way that competes with singular they? - No. This year the closest is “Xe - xe/xem/xyr/xyrs/xemself” (7.2%, compared to singular they’s 79.5%). Users of these neopronouns will probably not reach consensus for many years - language and especially pronouns can be very slow to settle and gain ground. Even if one neopronoun does become very commonly used, many will continue to use other neopronouns for a long time to come.

THIS YEAR IN REVIEW

Crowdfunding was successful enough that I have a little money leftover for costs next year. We had around the same number of participants as last year, but follower numbers and mailing list subscribers increased, which bodes well for next year.

I made some minor changes to the promotional illustrations to make them more gender-/sex-inclusive, and this year I got no complaints, so that was a good move! However, this year I did see a lot more confusion about who is invited to take part. I think the changes were probably worth it to make sure I’m being as welcoming and inclusive as I can be in the promotional stuff, so hopefully people will err on the side of caution and just jump in.

The way that the new survey software collects information, and my increased knowledge of Google Sheets, mean that I didn’t have to resort to MS Excel at all this year. This is really good, because working with unfamiliar software slows me down a lot! My formulae have been more efficient (thanks to my increasing Google Sheets skillz), so the entire sheet could be processed at once instead of being split into several questions. I’m really happy about that, because it means the entire worldwide results report came out less than 24 hours after the survey closed, instead of... *cough* eight months *cough* ...

I made an executive decision not to do a UK report this year, because the added complication makes it really hard for me to motivate myself. It definitely worked, look at that, it’s only March and the worldwide report is already out! I might still do a UK report, and I will keep collecting UK/not UK info about participants so that I always have that option, but for now I’ll just concentrate on the worldwide report and just do the UK report if I feel like it before 2020. And of course the spreadsheet is available to anyone who wants to download it and play with it, so if someone else wants to make some UK-specific statistics happen that is totally possible.

What I’ll do differently next year

In the identity question, I will keep queer as a checkbox option, but I will specify that it’s a gender. Maybe “queer (as gender identity)”? Feedback welcome on this!

In the pronouns question, I’ll change the wording of “none/avoid pronouns” so that it’s clear that it includes just using someone’s name. That’s because a lot of people tried to enter their names as neopronoun sets to express that, and I want to avoid people entering identifying information.

I will ask about age, to make sure that people over 30 are represented by checkbox options. Typically only about 10% of participants are over 30 so I want to make sure as many as possible are comfortable taking part. I’ll group ages into sets of 5 years (21-25, 26-30, etc.) to reduce risk of people being identified, and because entering an exact age probably feels a little more uncomfortable.

After 2020, any identity word, title or pronoun that is entered by less than 3% of participants and less than 3% of participants over 30 can be removed in future surveys. (I am a little concerned about this part, because it’ll make the work more complicated for me, and more work means more risk of epic procrastination. I’ll do my best!)

I’ve finally admitted to myself that I need to separate man and boy, and woman and girl. Currently it’s “woman (or girl if younger)” and “man (or boy if younger)”, and every year plenty of people skip those options in the checkboxes and type in “girl (but not woman even though I’m not a minor)” or something like that, and next year I’ll be asking about age so that’ll be an easy way to determine if there are any adults who are comfortable with one and not the other. This will increase the number of checkboxes to 30, which is pretty unwieldy and will make it harder yet again for people to find their words and increase the rate at which people drop out of the survey, so I’m glad for the under-3% checkbox removal threshold that I’m introducing from 2021 onwards.

Closing thoughts

I slipped up on a couple of things this year (ambiguity over the word “queer”, for example) - but overall I’m pretty impressed with how well I handled it all compared to last year. (I had recently moved house and was trying to rebuild my life, so I didn’t have a lot of spare energy in 2018!)

As always, I’m excited to pore through all your written answers and feedback, and I’m really grateful to everyone who shared the survey link! There were hundreds of RTs and thousands of reblogs, which never ceases to amaze me. Thank you everyone for sharing a small linguistic part of yourselves with me, I hope putting it all together helps you and makes a positive difference to the world!