I think you're slightly misunderstanding my point, which is that a huge spectrum of associative pattern seeking logics are embedded in language and that the LLM learns them and operates them, approximately.
"There is nothing to suggest that the training data somehow accidentally encoded biases related to fake tribes that the creators of the training data (i.e. ordinary people going about their ordinary Internet lives) somehow accidentally expressed."
This is exactly not what I'm suggesting.
I think it's less obtuse to make the point that there are social-prejudicial structures encoded in the latent space. "associative pattern seeking logics" is a bit incoherent, and distributional semantics doesn't live at a level accessible to cultural analysis and theoretics, IE film critique.
If you walked into a film theory class and posited that you could derive every single encoded interpretation of a film by memorizing the positioning of the actors and objects frame-by-frame, plus the audio track in another language that you do not speak, for every single piece of video ever made, you'd probably be asked to leave. Not that I'm advocating for the position of critique here, I don't think the anti-distributional semantics crowd is ever going to recover from their humiliation that's been accelerating over the last 8 years. It's just that from the position of critique it requires a coherent narrative that human brains are capable of ingesting (IE not maximal information overload).
If you really want to go the lower level route, I think Francois Laruelle's non-philosophie touches on what you might be thinking of in a much more robust way, shining a light on the unexamined consequences of decision and dialectics of-themselves. If you can stomach the writing of continentals, that is.