number one thing i want for public bathrooms is for them to be unisex accessible safe private and clean. number two thing i want for pubic bathrooms is for them to have flat surfaces in the stalls you can put your handheld items down on when youre shittin. ive encountered it in like two bathrooms ever and it changed my life for real.
many of our ancestors worked so hard to be not farming and I deeply appreciate that
I love not farming
I respect the hell out of farmers and I'm glad that's someone's dream. because it's sure not mine
I would not be taken in by the tradwife influencer grift about milking a cow in a sundress. I have been around cows. my uncle was a dairy farmer. I love not milking a cow. I love getting milk from a store. I love getting vegetables and fruit and meat and bread from a store.
would I rather it be a local farm's store or a local bakery or butcher shop? yes! maybe when I make more money!
I also think that the strength gap is at least partially manufactured women would in fact be stronger overall if little girls were encouraged to do physically taxing games and activities and eat their fill while they’re growing vs having to constantly diet and be sedentary indoors (or god forbid do intense cardio while under-eating). The amount of adult women honestly afraid to lift weights bc they think they’ll get bulky as though bulking isn’t a full time job that athletes have to spend all their time on and anyone on earth gets shredded from just using their adult muscles for their intended purpose, girl your bone density 🥀
if you say women are intentionally nerfed from birth in 2026 people look at you like you’re insane and start condescendingly telling you about how women are just better at different things (but not during their periods haha) but this was a completely basic feminist talking point I grew up with like “girls can do it too! [shot of little girls climbing and running with boys]” nickelodeon commercial tier base level I hate it how is everyone suddenly dumber than the average 7 year old
one time in my english class the teacher gave us a written assignment to basically explain how the book we were reading ended and this one kid just wrote “with a period” and he got full credit
my english teacher told a story once how he told the class to wrote a 5 paragraph essay on a brick and a student wrote “5 paragraph essay” and taped it to the brick and he got full credit and the teacher still has this brick
2. wilhelm marr popularized the term “antisemitism” as a more scientific-sounding alternative to judenhass (literally “jew hatred”) in the late 1800s, so for those of us with a sense of historical time that’s before the nazis. the term has only been used to mean jew-hatred.
3. are butterflies flies made of butter, or is that etymological fallacy?
4. okay enough time spent on this nonsense, i am going to eat frozen fruit
"the victims of the nazi holocaust are dead, and the legacy of that tragedy does not reverberate in the form of its victims' descendants"
this statement in and of itself is absolutely batshit insane, and provably false on both counts.
but then we get to the straight-up conspiracies.
"jews [...] disproportionately occupy the upper echelons of business [and] media"
"the powerful jewish capitalists that have the president's ear"
"jewish supremacy is as integral an arm (tentacle?) as white supremacy"
....
so of course, when they're not spouting protocols, they pull their favorite semantic trick:
"antisemitism [is] a collection of truths and lies thrown carelessly together. I suggest anti-Judaism, a more targeted approach that focuses on the contemporary iteration of the religion."
and thus we move from the old, outdated, physiognomy and race science based "anti-Semitism" (since of course "Semite" does not actually refer to "Jew", and jews aren't a race at all, except they kind of are because they're basically uber-white), to the straightforward term "anti-Judaism".
a clean, modern term, to reflect what "Judaism" clearly is: "a very real religion called judaism once existed [... it] has been thoroughly transformed, now existing as little more than a supremacist identity used to justify hierarchy and oppression."
great! so we've redefined what a jew is. we've redefined the term referring to jew-hatred--we've moved from an old, outdated term that doesn't really get to the heart of why we're hating the jews to our new term, one that cuts to the center of justifying our new wave of hatred.
now, there's only one thing left for us to do.
we know that a jew is a capitalist, an imperialist, not just a part of white supremacy but the foundation of it; a jew is everything we hate. "to be a jew is to be complicit." in what, you may wonder? in every societal ill--that is what complicity means.
and thus, our left-leaning, anti-capitalist writer who wants nothing more than to defeat the evil of the jew that "is tied on every level to global capitalism and imperialism", because of course doing that will finally lead to the socialist utopia of our dreams, must naturally come to the obvious conclusion that:
new conspiracy based on ancient conspiracy just dropped: the Jews are responsible for the plague (in this case, the hantavirus outbreak on a cruise ship). there’s been a lot of this on the app formerly known as Twitter, as per usual. no idea what the one referring to poisoning children with milk is referencing, though there is currently a formula recall.
Representing Jewish Communities In 100 Countries Across Six Continents
The first major instance of blaming Jews for spreading diseases in Europe dates back to the 14th century in the south of France, where Jews were accused of spreading leprosy to kill Christians. Both Jews and leprosy patients were murdered in the riots that ensued. Jews were perceived to be less affected by it than surrounding non-Jewish populations, possibly due to hygienic regulations required by Jewish law (frequent hand-washing and ritual baths). This claim led to pogroms, the murder of Jews, and even the expulsion of the entire Jewish communities of Strasburg (February 1349) and Spain (1492).
As the disease spread, killing 25 million Europeans--roughly 40 percent of the population--Jews were accused of spreading the virus through common drinking wells. Thousands of Jews were murdered in response.
Later, after the rise of Nazism, German propaganda described typhus, which is spread by lice, as a “disease characteristic of parasitic, subhuman people—the Jews” and blamed them for its spread. The Nazis used this to justify the isolation of Jews in ghettos, which in fact only increased the proliferation of the disease. This was one of the major motifs of the notorious film Der ewige Jude [The Eternal Jew], in which Jews were depicted as disease-bearing rats.
In Nazi propaganda, the notion of the “Jews” as synonymous with poison appeared in many forms, including in a children’s book published by Julius Streicher of the notorious Der Stürmer, who likened the Jewish race to a “poisonous mushroom” that is nearly impossible to contain. The Poisonous Mushroom remained available for sale on Amazon, accessible to all extremists looking to nourish themselves with hateful content, until earlier this year, when it was removed in response to WJC outrage.
A digital tool for studying the Holocaust through unique, original sources.
Translate Hate was created by American Jewish Committee (AJC) to explain antisemitism. This glossary aims to improve media literacy on antis
I teach veterinary and medical entomology courses. We cover hantavirus because no known arthropod vector transmits it, but because it's in rodents there's a lot of misconception that it can be transmitted like plague through insect vectors (there are some studies showing uptake of the virus in arthropod models, but no transmission).
Since this outbreak I have seen a ton of people engaging in conspiracy theories across social media. Everything ranging from rats don't actually exist in kitchens and thus it's a government plot to Jews poisoning the well.
People are extremely ignorant about how pathogens work, and extremely confident in their ignorance and conspiracy beliefs that they think they do.
The ignorance always feeds into conspiracy, and every conspiracy inevitably returns to antisemitism.
>Particularly among Gen Z, our data shows an interesting duality: they are both the group most likely to agree that women who have a successful career are more attractive to men but are simultaneously most likely to agree that a wife should always obey her husband and that a woman should never appear too self-sufficient or independent.
I know these two things seem contradictory, but there’s nothing a conservative man loves more than to tear off an angel’s wings. There are plenty of women that would willingly choose the obedient SAHM lifestyle, but these kinds of men always seem to go for the opposite. Why? Because it’s a power play. There’s no need to break a horse that’s already broken, and that would do nothing to validate that man, his ego, and his place in a world he sees as designed for him.
Another factor is that these men avoid dating conservative women who already want the lives they want them to have because those women's standards are too high. Specifically, such women expect to be the obedient stay at home mum, but they also expect their men to be the masculine ideal from the other half of the equation -- they tend to look down on their men if they cry, they expect them to be able to financially provide for the household, they want them to uphold their end of the bargain. You see this again and again in groups of conservative men who go out of their way to date liberal women; there is a power play, to tame someone untamed and bring her into line with his expectations, but there's also her lack of expectations of him. They want a woman who will do all the household and keep the home but ALSO will not reject him for not being able to afford to finance the family alone. They want a woman who'll respect and obey him but ALSO be fun and relaxed and let him show whatever emotions he wants. They want the Perfect Trad Wife who won't expect him to be the Perfect Trad Husband.
You see the same thing in conservatives who complain that all their leftie friends are abandoning them, but who won't just hang out with right wing friends instead. They don't want to hang out with other righties because a group of righties quickly becomes judgy and hateful and socially competitive, and is only fun to hang out with when they want to vent, whereas their leftie friends were more relaxed and fun. They want license to be unpleasant and expect unreasonable things of others, but want the people around them to be pleasant and not expect unreasonable things of them.
Text of tweet under the cut because it is loooong.
But... Stochastic Parrots.
Timnit Gebru was fired from Google in December 2020 for refusing to retract a research paper, and every single warning that paper made about large language models has now happened at a scale the industry spent 4 years trying to make people forget about.
Her name is Timnit Gebru.
She co-led the Ethical AI team at Google. She co-wrote a paper called "On the Dangers of Stochastic Parrots" with Emily Bender at the University of Washington and two other researchers. The paper was 14 pages long. It was submitted to a top AI ethics conference. And it was the reason Google decided that one of the most senior Black women in AI research could no longer work there.
The story Google told publicly was that she resigned. The story she told, confirmed by 2,695 of her colleagues in an open letter, was that she was fired by email while on vacation because she refused to either retract the paper or remove her name from it.
The paper had not even been published yet.
Here is what she actually wrote, and why every prediction inside it has now come true.
The first warning was about scale itself. Bender and Gebru argued that training ever-larger models on ever-larger scrapes of the internet would produce systems that appeared fluent but had no actual understanding of language. They called these systems stochastic parrots because they would repeat patterns from training data with statistical confidence and zero comprehension. The paper predicted that this apparent intelligence would fool both users and developers into trusting outputs that were structurally incapable of being reliable.
This was 2020. GPT-3 had just come out. The paper predicted the hallucination problem before anyone had a word for it.
The second warning was about bias amplification. The paper documented in detail that internet-scale training data contains systematic overrepresentation of dominant viewpoints and underrepresentation of marginalized ones. The models would not just absorb this bias. They would amplify it, because the optimization process rewards confident outputs, and confidence in language patterns tracks frequency in the training set.
The prediction was that hiring tools built on these models would discriminate against women. That healthcare triage tools would underperform on Black patients. That loan approval systems would entrench inequality while presenting their decisions as neutral algorithmic judgment.
Every one of those things has now been documented in deployment.
Amazon's hiring algorithm penalized resumes that contained the word "women" in any context. Healthcare risk scoring algorithms used by major US hospitals were found to systematically underestimate the medical needs of Black patients. Apple Card's credit algorithm gave wives credit lines 10x lower than their husbands for the same financial profile.
The third warning was about environmental cost. The paper calculated that training a single large language model produced emissions equivalent to the lifetime output of 5 cars. The prediction was that the race to scale would create an environmental footprint that would eventually rival entire industries.
In 2024, Google's emissions were up 48% from 2019, and the company explicitly blamed AI infrastructure. Microsoft's were up 29%, same reason. Both companies have now quietly abandoned the climate commitments they were publicly celebrating the year Gebru was fired.
The fourth warning was about documentation. The paper argued that the training datasets being assembled were too large for anyone to actually audit. Nobody at Google, OpenAI, Meta, or any other lab could tell you with confidence what was in the data their models were trained on. This was not a temporary problem to be solved later. It was a permanent feature of the approach.
In 2023, researchers discovered that the LAION-5B dataset, used to train Stable Diffusion and other major image models, contained thousands of images of child sexual abuse material. The companies that had trained on the dataset had no way of knowing. The paper predicted that category of failure 3 years before it was found.
The fifth warning was the one Google cared about most.
Bender and Gebru argued that the deployment of these systems would centralize linguistic and cultural power in the hands of the small number of companies that could afford to train them. The internet would become a place where the dominant voice was a statistical average of dominant voices, presented as a neutral assistant. Languages underrepresented in the training data would degrade over time as more web content was generated by these systems and fed back into the next training run.
This is now happening in real time. A 2024 study found that 57% of new web content in English is AI-generated or AI-assisted. Researchers studying low-resource languages have documented active degradation in translation quality, because the synthetic content fed back into training is itself worse in those languages.
The paper Google fired her for predicted the model collapse problem before model collapse had a name.
The mechanism behind why this all happened is the part of her work that nobody quotes.
Gebru's argument was not that AI is dangerous in some abstract sci-fi sense. Her argument was that AI is dangerous in a very specific structural sense. The technology was being built by a small group of researchers who shared similar backgrounds, worked at similar companies, and were rewarded for shipping products faster than competitors. The incentive structure made it impossible for safety, ethics, and bias concerns to slow anything down. Anyone inside the system who raised those concerns was either ignored, sidelined, or removed.
She was making that argument from inside Google.
Then Google proved her right by removing her.
The team Google had built to make sure their AI was safe was dismantled in 90 days because they did the job they had been hired to do. Margaret Mitchell, the other co-lead of the Ethical AI team, was fired two months after Gebru for searching through her own emails for evidence of how Gebru had been treated.
Gebru did not stop. She founded DAIR, the Distributed AI Research Institute, in 2021. The mission is to do AI research outside the control of the companies that have a financial interest in not hearing the answers.
Every prediction in the Stochastic Parrots paper has now been validated by deployment. Hallucinations are an industry-wide problem the largest labs cannot solve. Bias amplification has been documented in hiring, healthcare, lending, and criminal justice. Environmental costs are larger than entire small countries. Training data audits remain impossible. Model collapse is an active research crisis at every major lab.
The question worth sitting with is the one almost no one in the industry will say out loud.
Every researcher with the technical credibility to call out these problems watched what happened to her in December 2020 and made a calculation about their own career. The number of people willing to speak publicly about safety and ethics issues inside the major AI labs collapsed after that firing and has not recovered.
The researcher Google fired for warning about exactly what is now happening was right.
The company that fired her is now the second-largest deployer of the technology she warned about.
And the people inside that company who agree with her are not allowed to say so.
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