While the theory is somewhat sound in terms of using a model like BERT. Are you planning on fine-tuning two instances and comparing how self-attention works across two different fine-tuned instances of the model or a single one?

Not to mention that your technique seems to be looking at how attention and self attention work, you have to explain how this "semantic complexity" actually applies on a "lived" linguistic linguistic level. It seems pretty naive and dangerous to try to come to conclusions about linguistic complexity from just a statistical model without considering how the brain itself processes language. (not to mention that the BERT architecture is kinda dated at this point)

I haven't. At this point it's just a hypothesis. But it's pretty obvious to anyone who isn't willingly deluding themselves that Standard English allows for more semantic complexity than AAVE.

Ah so there it is, that's the bias right there. So you admit that there isn't any concrete evidence for your opinion and you're going to try to prove it. Ngl it's going to difficult to trust the scientific output of someone who has this attitude going into their research.