There seems to be very few cases where ICL is really doing something that can be considered as learning (albeit ephemeral) rather than just utilizing in-context data via induction heads.

Yes, I'm aware of the linear regression example, and a few others, but these appear to just be specific capabilities that were learnt during pre-training, presumably pursuant to reducing errors on similar-but-different training samples, not any kind of generic run-time learning capability.