hi bi, i'm dad

Truncated text of tweet from MrPitBull, Mar 11, 2026:

She kept finding women in laboratory photographs from the 1800s. Then she read the published papers—and every single woman had vanished. Someone had erased them from history.

Yale University, 1969.

Margaret Rossiter was a graduate student studying the history of science. She was one of very few women in her program.

Every Friday afternoon, students and faculty gathered for beers and informal conversation. One week, Margaret asked a simple question: "Were there ever any women scientists?"

The faculty answered firmly: No.

Someone mentioned Marie Curie. The group dismissed it—her husband Pierre really deserved the credit.

Margaret didn't argue. But she also didn't believe them.

So she started looking.

She found a reference book called "American Men of Science"—essentially a Who's Who of scientific achievement. Despite the title, she was shocked to discover it contained entries about women. Botanists trained at Wellesley. Geologists from Vermont.

There were names. There were credentials. There were careers.

The professors had been wrong.

But Margaret's discovery was just the beginning. Because as she dug deeper into archives across the country, she found something far more disturbing.

Photograph after photograph showed women standing at laboratory benches, working with equipment, listed on research teams.

But when she read the published papers, the award citations, the official histories—those same women had disappeared. Their names were missing. Their contributions erased.

It wasn't random. It was systematic.

Women who designed experiments watched male colleagues publish results without giving them credit. Women whose discoveries were assigned to supervisors. Women listed in acknowledgments instead of as authors. Women passed over for awards that went to male collaborators who contributed far less.

Margaret realized she was witnessing a pattern that stretched across centuries.

Women had always been present in science. The record had simply pushed them aside.

She needed a name for what she was documenting.

In the early 1990s, she found it in the work of Matilda Joslyn Gage—a 19th-century suffragist who had written about this exact phenomenon in 1870.

In 1993, Margaret published a paper formally naming it: The Matilda Effect.

The term captured something that had been hidden in plain sight for generations. Once you knew the term, you saw it everywhere.

Her dissertation became a lifelong mission.

For more than 30 years, Margaret researched and wrote her landmark three-volume series: Women Scientists in America. She examined letters, institutional policies, individual careers. She gathered undeniable evidence that women in science had been consistently under-credited and structurally excluded.

Her work faced resistance. Many dismissed women's history as political rather than academic. Others insisted she was exaggerating.

Margaret didn't argue emotionally. She presented data. Documented cases. Patterns repeated across decades and institutions.

Eventually, the evidence became undeniable.

Her research helped restore recognition to scientists who had been erased:

Rosalind Franklin, whose X-ray work revealed DNA's structure—credit went to Watson and Crick.

Lise Meitner, who explained nuclear fission—omitted from the Nobel Prize.

Nettie Stevens, who discovered sex chromosomes—received little credit.

Cecilia Payne-Gaposchkin, who discovered stars are made of hydrogen—initially dismissed.

And countless others whose names had nearly vanished.

Margaret changed the narrative. Science was no longer just the story of solitary male geniuses. It became a story of collaboration that included women who had been written out.

There are a number of tells, but this is an excellent example to talk about em-dashes, which people often either take as permanent AI tells or run the other way and say "humans use em-dashes and that's why AI does, too! they're not tells!" Both are kind of right and both are kind of wrong.

What you'll see if you look closely at this text is that it ONLY uses em-dashes. Every time it needs to put in some kind of break or set off some text, it goes for the em-dash. There are no phrases in parentheses. There are commas, but only in places where the absolute rule is to use a comma (like in a series, for instance). There is one colon, again placed where the absolute rule is to use at (at the top of a list). Whenever there's an option, where a human writer would be actively making a choice about what punctuation to use, the AI defaults to an em-dash.

On top of that, look at the content. The AI bot people are obsessed with feminism, ironically. I suspect it's because very basic feminist narratives about women pushing back against barriers or doing something heroic are popular and gets shared widely. So, first of all, you should be on your guard when you see a "what this woman did CHANGED HISTORY!" kind of piece. (I wonder if the twitter/tumblr trend of BUCKLE UP history posts has affected the AI ...) And then you should check out the specific claims.

She kept finding women in laboratory photographs from the 1800s. Then she read the published papers—and every single woman had vanished. Someone had erased them from history.

I can't find this anywhere else. The paper "The Matthew Matilda Effect in Science" doesn't talk about photos! The Wikipedia page doesn't talk about photos! This Smithsonian article doesn't talk about photos! Her piece on her career in Writing and Revising the Disciplines (2002) (good read) DOES mention photos, in that she got the Mount Holyoke archivist to send her a few from the 1880s showing women doing scientific work as a nice illustration that "epitomized" what she was already aware of.

Rossiter started with textual primary sources that documented women as named individuals contributing to scientific discoveries. The idea of her being confused by photos is a hallucination.

Despite the title, she was shocked to discover it contained entries about women. Botanists trained at Wellesley. Geologists from Vermont.

There's definitely something to be said about the framing of this bit as shocking!!! but since I'm talking about facts and sources, it's clear to me that the AI recognized the botany-Wellesley connection from the paper but could not parse that the reference was to a female botanist who taught at Wellesley. There is also nothing in the paper about Vermont geologists, so I have no idea where the AI got that; I would suspect it's another hallucination attempting to create a pattern from the first reference.

But Margaret's discovery was just the beginning. Because as she dug deeper into archives across the country, she found something far more disturbing. Photograph after photograph showed women standing at laboratory benches, working with equipment, listed on research teams. But when she read the published papers, the award citations, the official histories—those same women had disappeared. Their names were missing. Their contributions erased.

Again, back to the mysterious photographs. But the rest of this text is an issue as well: what Rossiter describes in the paper is not a complete absence of these women in any official documentation, but that these women were amply documented and known to be working within the scientific community and yet did not receive public credit or awards. It's not a complete smothering out, but a sort of complacent back-burnering, which is too nuanced for the AI to be able to handle when told to "write a post about the Matilda effect that will get engagement on social media". She didn't prove that discoveries attributed to male authorship actually had women involved and only she knew their names: she collected many stories that people already knew of overlooked/underplayed female scientists and put them together to say, "This is a pattern and we should have a name for it." Some of her examples were even recent enough (1970s-80s) that she was able to point to a feminist backlash.

And again ironically, the AI itself engages in the Matilda Effect by presenting this whole thing as utter silence -> Rossiter gets curious -> the case is blown open. Rossiter actually refers to the work of other female historians and social scientists! In fact, she started this line of research after noticing the female biographies in American Men of Science when her housemate, Cynthia Thompson, recommended that she keep track of them.

Her research helped restore recognition to scientists who had been erased: Rosalind Franklin, whose X-ray work revealed DNA's structure—credit went to Watson and Crick. Lise Meitner, who explained nuclear fission—omitted from the Nobel Prize. Nettie Stevens, who discovered sex chromosomes—received little credit. Cecilia Payne-Gaposchkin, who discovered stars are made of hydrogen—initially dismissed. And countless others whose names had nearly vanished.

Rossiter did not claim to be rediscovering these women. She refers to Franklin and Meitner as having been famously denied credit, in fact! Meitner specifically is "one of the best-known examples of the phenomenon". Stevens she uses as one in the list of examples in the paper, and Payne-Gaposchkin actually just gets a reference at the end that's doesn't even tell you the specific field of scientific study. (To be fair, there may be more about them in her other publications.) This was not about Badass Historian of Science Tells the Establishment What's What. Everybody knew about the concept of female scientists being publicly ignored as collaborators by 1993 — and women's history as a field had been around for 15-20 years. She was not working in a vacuum where nobody else thought that it was important to study these topics until she forced them to see the light.

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All in the Wangxian Family by tungstenpincenez (G, 19k, Fanwork Research & Reference Guides, family tree, Comic-Con, Humor, tutorial, Chinese names, chinese honorifics, warning: mental illness discussion)

🔒 Writers Guide: The Guqin by ThisIsWhereTheMagicHappens (Not Rated, 1k, Fanwork Research & Reference Guides, Writers, guqin, chinese instrument, Meta, non-fiction)

How Mo Dao Zu Shi Uses Classical Chinese Literature and Ideas in Character- and World-Building by yakuzakuma (G, 5k, Reviews, Meta, Fanwork Research & Reference Guides)

Working Guide to almost every single mxtx character by Nightfeather18 (M, 1k, all the characters, every single one, help guide, Spoilers, my horrible sense of humor)

🔒 On Character’s Ages by thewickling (Diviana) (G, 5k, Fanwork Research & Reference Guides, Meta, Nonfiction, Cross-posted on Dreamwidth)

🔒 On Qishan Indocrination’s Duration by thewickling (Diviana) for pumpkinpaix (G, 1k, Fanwork Research & Reference Guides, Módào Zǔshī History, Qíshān Wēn Indoctrination,Timelines)

🔒 A Compiled List of Known Lan Clan Rules by Unforth (Not Rated, 2k, Meta, Fanwork Research & Reference Guides, Nonfiction, Cross-Posted on Tumblr, Podfic by dangercupcake)

A Writer’s Unofficial Guide to Chinese Naming by FireflyPie (G, 2k, Fanwork Research & Reference Guides, Chinese Language, no knowledge of the MXTX novels strictly required)

🔒 List of Differences Between Modao Zushi and CQL/The Untamed by Unforth (Not Rated, 3k, Meta, Fanwork Research & Reference Guides, Nonfiction, Cross-Posted on Tumblr)

🔒 The Untamed / MDZS, resources link post, stuff I needed as a writer by AteanaLenn (G, 1k, Meta, Metafiction, resources, linkdrop, Nonfiction, Fanwork Research & Reference Guides)

Chinese naming basics for fanfiction writers by miqqumi (Not Rated, 937, Meta, Fanwork Research & Reference Guides)

🔒 MDZS Timeline by thewickling (Diviana) (G, 22k, Fanwork Research & Reference Guides, Meta, Nonfiction, Módào Zǔshī History)

Grandmaster of Demonic Timeline by chrisemrys (G, 2k, timeline, Fanwork Research & Reference Guides)

MDZS Audio Drama Episode Guide by pumpkinpaix (Not Rated, 5k, Fanwork Research & Reference Guides)

Mo Dao Zu Shi Writer Reference: Novel Chapter Summaries by threerings (Not Rated, 2k, Fanwork Research & Reference Guides, Podfic by dangercupcake)

Reference for Modao Zushi Writers: Chinese terms by chaoticjoy (G, 3k, WIP, Meta, Fanwork Research & Reference Guides)

🔒 MDZS History Context for Dummies by enbysaurus_rex (Not Rated, 14k, WIP, Meta, Analysis, Historical Accuracy, Historical Metaphors)

Ghostbusting Economics: The Great Cultivator Labor Shortage by GhostySword (G, 3k, Meta, Economics, Worldbuilding, Crack, Though honestly it’s not that wild and pretty well supported by the text)

RL Cultivation 101 by Gina3 (T, 2k, Meta, cultivation, Taoism)

Fanwork Research & Reference Guides tag on AO3

WangXiantics: The (unofficial) Untamed Episode Guide by Trensu (T, 116k) although it’s a reaction work, it also serves as a list of episode summaries highlighting key moments.

meta and translation masterpost by @songfeng-shuiyue

The Reading of Sorrow (and other works) by Tavina (T, 10k, WIP, Meta, Worldbuilding, Yuan Dynasty (1271-1368 CE), Essays, Research, Historical References, Historical Accuracy, Chinese Mythology & Folklore, Yuan Dynasty Paintings and Painters, Future Fic, Appendixes, Music) historical research underlying the fic but I’m not in charge of sorrow (so please don’t ask me when) with abundant book recs.

Who Knew the Truth About the Wen Remnants? by Karmiya (T, 8k, Meta, Essay)

~*~

Google Docs

transcripts and translations for the entirety of The Untamed (Spreadsheets)

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~*~

Maps of MDZS

Twitter thread by @/wangxianling

Twitter thread by @/bosbiee

Stunted, Starving Juvenility - Addendum by TomatenMark

Highlights include:

For your first two years (when you were small) you lived in a foster home with people who raised you into a very polite young man. Two is like you plus me, that's what two is.

Some people adopted you before me and they called you Timmy (which is a stupid name) and they returned your ass almost immediately because you were so annoying at that age.

Like think about how annoying you are right now at seven years old, but way worse.

I'm better than them though, I don't call you Timmy and I wore earplugs to bed for three years because you love to scream at bedtime. Earplugs are like when I roll over and go back to sleep even when you are yelling so so so loud.

I got you at a time in my life when I was really sick (being sick is like when I'm up late because I'm throwing up and you are a very handsome good boy who sits with me) and they had to put me asleep for a procedure. A procedure is like what happened to you when they put you asleep and took your balls away.

I put together a relatively short survey (about two dozen questions, mostly multiple choice, all optional) to get some data on what fic lengths and completion statuses readers on AO3 prefer or avoid. If I get enough answers to have a good sample size, it should give us some insight into how people search and read on the archive.

If you find this interesting, feel free to share it with AO3 users elsewhere or post it to other platforms. I'd like to get a good crossection of readers that isn't biased by platform, if at all possible.

The survey is just for fun/curiosity, and isn't associated with any university, company, or other entity. It's just me asking you this stuff here :)

When I filled this survey out initially, I ran some quick and dirty math on a bit of data I had on hand about the number of fics I was reading, sorted by word count. However, I was a little surprised to find the percentages that approach yielded didn't really seem to reflect my own intuitions about what I normally prefer to read.

By my own estimation, my favorite fics to read are normally between 10k-50k words. According to the data I was looking at, though, the number of shorter fics seemed much higher than expected. Upon reflection, though, that actually made sense; after all, short works are much easier to burn through and get out of the way. Intuitively it does feel like I spend much less time reading these types of fics, but they're shorter in the first place, so that could still be true.

This reasoning led me to conclude that maybe it would help to collect some more granular data and work out how many total words I actually read in each word count sub-category. So... I decided to look at every ao3 bookmark I have ever created and sort those numbers for a better sample size. I'm sure there probably is a way to export this data as a csv or something, but I just copied them manually into a big spreadsheet. (This process had me stopping to revisit several old favorites along the way... so did take me a couple extra days for me to get through the whole list LOL.)

From there, I grouped the list into works between 1-5k, 5-10k, 10-20k, 20-50k, 50-100k, and 100k+. I generated a sum of the word count subtotals for each of those groups, then visualized the data in a pie chart.

Et voila!! Indeed this visualization was way more useful. It initially looked like I read more in the 5-10k category than any other, but as it turns out I sank more than double that amount of actual reading into the 20k-50k zone. That validates my subjective feelings about what I spend most of my time reading much more than the "number of fics" metric. Here's how they compare:

vs:

......Kinda crazy how different those seem, right?! Check out that 1-5k pale blue slice before and after. And the >100k blue slice as well! That's wild.