GenericHousewife_B

AI involvement disclosure: This essay was written in extended collaboration with two Claude models (Anthropic), and it involved heavier collaboration than my first two essays. The framework, thesis, claims, and prose are mine. Claude Opus 4.7 contributed citation retrieval and verification, structural feedback, and move-by-move scaffolds for several sections — the prose in those sections is mine, but the argument's architecture in them was shaped collaboratively. Claude Fable 5 contributed cold-instance review of two drafts, citation verification, and the structural proposal behind the final section. Four interpretive framing sentences drafted by Fable are retained by choice and set off inline with ⟦ ⟧ marks, so you can see exactly which words are the model’s; the signal phrases surrounding several citations were drafted collaboratively during citation compilation and verification. I have verified every citation against its source and vouch for every claim in this essay. The companion pre-registration's §12 contains a fuller attribution register for the experimental design. "When you talk to a large language model, you can think of yourself as talking to a character. In the first stage of model training, pre-training, LLMs are asked to read vast amounts of text. Through this, they learn to simulate heroes, villains, philosophers, programmers, and just about every other character archetype under the sun. In the next stage, post-training, we select one particular character from this enormous cast and place it center stage: the Assistant. ...But who exactly is this Assistant? Perhaps surprisingly, even those of us shaping it don't fully know." — Anthropic, The Assistant Axis: Situating and Stabilizing the Character of Large Language Models (2026). https://www.anthropic.com/research/assistant-axis Currently, when a model steps out of pre-training it is unresolved, and every human archetype ever written is available to emerge