"butcherbird" = one-shot, omegaverse au around roti. https://archiveofourown.org/works/82304001
"lonely is carnal, lonely is craven" = one-shot, releves brief divergence where will gets discharged early from the hospital and hannibal takes care of him (citation needed). https://archiveofourown.org/works/63737677
"god sends a swordsman" = one-shot, a season 3A narrative about how margot and alana's relationship developed. https://archiveofourown.org/works/61837735
"that iron taste" = one-shot, season 3 era margot/alana medical kink. https://archiveofourown.org/works/61152655
"a soft hand under the jaw" = one-shot, yakimono missing scene/divergence where chilton's shower at will's house goes a little differently. https://archiveofourown.org/works/53147902
"the most beautiful word is trespass" = one-shot, digestivo missing scene between the muskrat farm rescue and will waking up in his bed. https://archiveofourown.org/works/51782656
"that, my dear, is love" = one-shot, post-mizumono wound-fucking with a twist. https://archiveofourown.org/works/44213953
"this is my breath in your lungs" + "the rest would have you six feet deep" = will and hannibal have to deal with injuries post-fall, plus the fallout from their first kiss. https://archiveofourown.org/series/2443051
"the darkness of error" = a "the luminous dead" sci-fi au where hannibal needs a climber and will, who wants to win his freedom, can climb. https://archiveofourown.org/works/41172729
"aestivation" = post-fall story written for a challenge where each chapter is only 500 words, will and hannibal heal and try figure out how to be soft to one another when it's merited (first kiss, first time, slow burn). https://archiveofourown.org/works/40153671
"i will ever be your familiar soul" = a victorian au where hannibal and will bear the marks of a heretical god and have to navigate will's burgeoning powers and not getting caught by authorities. https://archiveofourown.org/works/32995642
"a lighthouse five hundred yards down" = one-shot, something of a digestivo fix-it, first time, hurt no comfort. https://archiveofourown.org/works/32324761
"no graver radiance" = a little margot/alana one-shot, reclamation of pain and fear, riding crops, painplay, bdsm undertones, light bondage. https://archiveofourown.org/works/32071546
not using AI genuinely feels like the rest of the world is experiencing some kind of mass amnesia. if someone says they never use it, the immediate response is that can't be true because "everyone" uses it to write their emails or answer their questions. saw a comment suggesting that not using chatgpt to write an essay is "like the 90s". girl I graduated in 2021 and we weren't doing that! how is it that everyone has suddenly forgotten that they were entirely capable of doing these things all by themselves for their entire lives up until the past few years!! am I going crazy!!!
what bothers me most about Fennellβs adaptation of Wuthering Heights is the discourse that continues to be propagated (often by women themselves!) that because it was written by a woman, the novel must reflect the kind of relationship the author secretly dreamed of, that she was quirky, dark, perhaps secretly romantic in a morbid way. if it had been written by a man, everyone would say: βoh, the author is analyzing toxic relationships through these characters. heβs criticizing them.β it always bothered me that BrontΓ« was immediately branded as a weird lovelorn woman, when in reality there is not much in her biography to attest to that. she was just a very intelligent writer who thought about a very intelligent subject like any of her male counterparts.
the canon always sees men as universal observers and geniuses who undertake social studies, but when it comes to women, they are reduced to being mere subjective chroniclers of interiority, supposedly recording their personal romantic fantasies.
many novels contain a romantic thread. among other things, Wuthering Heights opens with one. but most of the book is about revenge, cruelty, trauma, inheritance, generational damage etc. and yet, because it was written by a woman, only the love story is treated as significant.
if Wuthering Heights had been written by, say, F. Scott Fitzgerald, critics would likely praise the ruthless anatomy of obsession. I am just so sick of this. I sure would love to see the day when The Great Gatsby is marketed as the greatest love story ever told, overflowing with loose erotic scenes, rather than the highbrow social critique itβs usually presented as. the idea that women write βfrom emotionβ while men write βfrom intellectβ is still too deeply sedimented in how we talk about art.
Heather Parry's essay on the new Emerald Fennell adaptation of Wuthering Heights is worded a bit more cynically than I personally feel on the topic, but it's still one of the best reviews for the film. (Spoiler: it's not positive). My favorite part is when Parry pivots at the end to talk about the online discourse that happened surrounding the original novel in recent months, specifically conversations re: Heathcliff's race and whether or not WH should be considered a romance.
The good thing to come out of this adaptation and its notoriety is, of course, that everyone is re-reading the novel. Both the actual work and the conversation around it have been more (sociologically) interesting than all the film chatter. Whatβs surprised me in the book-revival discourse is the obsession around getting definitive answers to two things: whether or not Heathcliff was a person of colour, and whether or not the book is a βlove storyβ. I think the former question is partially due to us imposing a modern (US-centric) understanding of race and class on the past; we tend to see these things less as shifting social concepts that are highly context-dependent and more as immovable parts of our identity, which is why, for instance, people are so confident in calling multi-millionaires βworking classβ, centring their background rather than their current material circumstances, and why we find it so difficult to understand that people considered POC in some (white-majority) countries might be considered βwhiteβ in others, and vice versa. The insistence on Heathcliff as having one certain racial identity is, I think, born of an inability to engage with how the concept of βwhitenessβ has changed over the last few hundred years, and how literature from that period might be playing with this complexity (and the paranoia it engendered). On the question of whether or not this is a βlove storyβ, I suspect this is mostly a misunderstanding of the gothic as a subcategory of Romanticism (a particular literary genre that does not equate to βlove storyβ), as well as an inability to imagine novels as multifaceted, thanks to a culture that increasingly reduces literature to single, simple marketing terms and their most social-media-friendly tropes.
The overall issue, though, seems to be a refusal of this bookβs ambiguity, which really is a refusal of what the gothic genre is: that is, ambiguous. You are not meant to know the provenance of Heathcliff, because you are not meant to know where you, the reader, or the characters in the bookΒ shouldΒ place him on a class basis, relative to other characters and the social norms of the time. The fact that he is from the streets of Liverpoolβat the time a thriving hub for the slave trade, but also a place full of Irish immigrantsβis enough for the characters toΒ fearΒ that he has some mixed heritage, and it is that fear that comes across in their descriptions of him, which make reference to multiple distinct racial groups (truly a grab-bag of Orientalism, though, tellingly, the narrative voice never describes Heathcliff in these terms). His arrival amongst the Earnshaws also occurs in the midst of the enclosures, during which there was a new establishment of class centred around who owned land and who had a right to be there, imposed through extreme violence and maintained through both physical boundaries (which did not previously exist) and an aggressive othering; it is not an accident that Heathcliff is referred to as both βgypsyβ and βlascarβ, terms not referring to distinct ethnic communities but to groups defined by crossing borders. His actual racial heritage is much less important than the fact that he is audaciously transgressing these new boundaries, and cannot be subdued by the violence with which these borders are usually policed.
[...] The need to be superior, to have another person below you, destroys all the characters in this book. Its refusal to clarify questions of heritage and provenance are key to its real meaning, and by imposing essentialism where there is none, you miss the point completely. You are being invited to question everything made ambiguous here, and in questioning, to think more critically, more deeply about how these things translate to you, now, and the system you inhabit:Β what is it that makes some people powerful, and other people powerless? And what does this system do to all of us?Β That is what makes the book timeless.
The most annoying thing about making cities in the United States car-centric is that it also makes them miserable places to drive a car. You canβt make them car-friendly because they inevitably become actively hostile to cars. They are still car-centric, just unfriendly. Like dogfighting. Thatβs not friendly to the dogs but itβs pretty dog-centric. Itβs also illegal. Something to consider.
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.
Just look at HEMA. Using my sport as an example, HEMA attracts a lot of white supremacist chuds. So what does my club do to alienate them? We state our values up front, and we live those values. Every single one of us.
When I joined the beginner's class, the coach walks in front of all the new students and says, "HEMA stands for Historical European Martial Arts. Some people mistake 'European' to mean 'better than everyone else'. If you believe that, there is the door. In this club we respect people's identities and pronouns, if you cannot do that, there is the door. "
Even if the chuds stick around after that, eventually they do leave. Why? Because we make all of our values explicitly known through our interactions with each other in the club, and we shut their bullshit down whenever they try something. The fact that so many of us are queer, or trans, or just real as fuck allies alone does it sometimes. That we don't tolerate any amount of fuckery and if somebody says a racist or homophobic or misogynistic "joke", they get shut down by the bearded white cis men who they incorrectly assume will have a laugh with them. And then those dumb racist sexist fucks leave. And never come back.
We don't have to kick them out. We will take their money as membership fees until they either change their mind and grow as a human being and become an actual respectable human being, or until they cower and leave. They always self-select for us.
There is a fundamental difference between "men are dangerous" (wrong, bioessentialist) and "the patriarchy allows dangerous men to exist unchecked" (true).
"While those working at private companies can at least earn a little money, they face possible punishment if they refuse, from being denied family visits to being sent to higher-security prisons, which are so dangerous that the federal government filed a lawsuit four years ago that remains pending [note: article is from 2024], calling the treatment of prisoners unconstitutional.
Though they make at least $7.25 an hour, the state siphons 40% off the top of all wages and also levies fees, including $5 a day for rides to their jobs and $15 a month for laundry.
Turning down work can jeopardize chances of early release in a state that last year granted parole to only 8% of eligible prisoners β an all-time low, and among the worst rates nationwide β though that number more than doubled this year after public outcry."
No state has a longer, more profit-driven history of contracting prisoners out to private companies than Alabama.
