Kungfunurse

John calling Harold with what he truly believes will be his final moments. Thanking him with his last breaths.

Harold breaking the speed limit trying to get to him in time even as John tells him to stay away, stay safe.

Joss staring at the two of them, John bleeding in Harold's arms, as all the pieces start clicking into place.

Harold's look of absolute desperation as he waits to see what Joss will do.

Joss making the monumental decision to let them go. Helping them escape.

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.

I thought I could never care for anyone again, until I met you.

love my pumpkin

Let's take as an example one line spoken by a dragon prince from a story set in fantasy ancient China:

translation version 1: Those ignorant humans sure know how to tell tall tales.

translation version 2: Those ignorant humans sure know how to bullshit.

Now which line do you think is more localised? Version 2 might sound tonally jarring given the setting, and it might seem more localised because it uses modern slang, but it's actually a more literal translation of the original sentence 這些無知的人類真會放狗屁, and this is because, as I explained in that other post, Chinese internet fiction frequently mixes contemporary slang with archaic language, which isn't something readers of English fiction are used to. So internet slang in historical/fantasy danmei doesn't always equal more localisation; on the contrary, an English translation of historical/fantasy danmei that reads tonally very consistent and which always uses language appropriate to the historical setting might actually be the result of localisation.

AU where BEFORE it’s too late, Nate turns to crime specifically to fund Sam’s treatment. Pulls together a crew of people he knows are good because he’s chased them all before. Does a heist, gets the money, Sam gets better.

And I don't think he'd ever be able to keep Maggie from finding out for long. She's incredibly sharp and knows him very well. I feel like Second David Job scenario would play out within half a dozen jobs *at the very least*, and I wouldn't be at all surprised if it happened by the second or third job.

That said, the idea of him breaking in time to save Sam, and of trying to have both family/respectable IYS job and Robin Hood crew thereafter? Totally fits for me. I'd love to see whether his marriage with Maggie would survive the difference between his self-righteous crusade and her more conventional ethics. Would she stay in the world, begging him not to go where she couldn't follow? How much would Nate waver from the life of crime when he has a living son who might find out and be ashamed of his father? Would Sophie, and the rest of the crew, start interfering to try to pry Nate away from his family, and would they start succeeding, or just blurring the lines further between the sides of Nate's double life? (I will admit that I'm very curious whether Sophie and Maggie could end up falling for each other and dragging a blushing Nate into a polycule. But mostly bc I'm very fond of Maggie and Sophie's canon relationship and a polycule is the only way I can see them getting along with Nate still married and Nate/Sophie still in the cards. Mostly. Also a bit bc I like their canon relationship when they team up against Nate, because they both recognize that that man needs some pragmatism to ground his ideals.)

Also wondering if Nate and Sterling would be friends, ex-friends, rival coworkers, or what. I suppose ideally all of the above. Given how willing Sterling is to work with the Leverage crew when it suits his own ends in canon, how long till he has a reason to engage them in this version?

The Confession

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2026/06/29/arsonist-firefighters/#im-feeling-lucky

Write a critical AI book, and you become everyone's confessor for their AI sins. People in my life keep telling me about their guilty AI pleasures, in search of an explanation, absolution or7 condemnation:

https://us.macmillan.com/books/9780374621568/thereversecentaursguidetolifeafterai/

Their most common confession: "I only ever use Google's A7I-generated search summaries these days. I no longer click those blue links beneath it, not even to verify the summary." People know that the summaries are full of "hallucinations" (that is, "defects" or "errors") but the summaries are right often enough that many people have come to rely on them, to the exclusion of actual websites, made by actual people, on the actual internet.

Everyone knows this isn't good. The reason there's a web for Google's Gemini AI to summarize is that Google – the thrice-convicted monopoly search company with a 90% market share – directs people to websites, and when you visit a website, you generate revenue for the site, which pays for its maintenance. Most commonly, you generate an "ad impression," but you might also buy a subscription, or generate an "affiliate fee" by purchasing a recommended product.

When Google strips all this away by harvesting an "answer" and displaying it at the top of the page, the bargain between Google and the open web breaks down. Google is extracting 100% of the value from the websites it summarizes, and giving nothing back in return.

This is a marked reversal from Google's founding ethos. In the old days, Google measured its success by how little time you spent on its site. The ideal Google outcome was for you to visit its page (or even better, just a search-box in your browser), type a few words, and get "ten blue links" back, the top one of which was the correct link to locate the information or resource you were seeking. The point of Google was to serve as a conduit, a trusted intermediary that neutrally adjudicated the relevance of every web page for every web user from moment to moment.

Everyone dunks on Google for its high-minded motto, "Don't be evil," but over the years, the company's mission was far more important: "Organize the world's information and make it universally accessible and useful." That was the pole star that googlers followed for the first couple decades of the company's history…until, that is, the company saturated its market and its growth stalled out.

That was when Google started to panic over its plateauing search revenue, this being an inescapable consequence of 90%+ market-share. The ensuing power struggle pitted googlers who were committed to technical excellence against the company's most ardent enshittifiers, who pointed out that by making search worse, they could increase revenues. After all, if you need to search two or three times to get the answers to your questions, that means the company can show you two or three times as many ads:

https://pluralistic.net/2024/04/24/naming-names/#prabhakar-raghavan

Where once Google measured its success by how quickly it could send you away from its site and out into the open internet, today's Google is a sticky-trap full of ways to keep you inside its walled garden.

A decade ago, tech had three major approaches:

I. Google's: let you do anything you want, but spy on you while you do it;

II. Apple's: strictly control what you can do, but leave you alone to do it in private; and

III. Facebook's: control everything you do, spy on you from asshole to appetite.

Today, tech is undergoing a form of carcinization, in which every company is turning into a Facebook-crab: maximally surveillant and maximally controlling.

Apple has added surveillance to its walled garden:

https://pluralistic.net/2022/11/14/luxury-surveillance/#liar-liar

While Google has turned its free-range, internet-wide surveillance system into a walled garden that tries to keep you away from the open internet as much as possible.

Now, in Google's defense, the "open internet" kind of sucks these days. Any piece of useful information you seek out on the open internet is liable to be buried under half a dozen pop-ups, pop-unders, and dickovers:

https://daringfireball.net/2026/05/what_is_a_dickover

Even after you clear these away, the actual information you're seeking is further buried in word-salads that anticipated insipid AI prose by half a decade. Think of all those omelet recipes that appear beneath 2,500 words of cod-Proustian remembrances of "the first time I ate an egg."

The major advantage of AI search summaries is in shielding you from all this nonsense. But where did all that nonsense come from in the first place?

It turns out that this is largely Google's fault.