[elandau25]

Fair enough, but target data in this sense IS a full distribution of Batmen. This approach is towards the goal of creating a broad dataset and fitting a full Batman model. We are training on a narrower subset of our actual target data and fitting to that narrow subset, whether you want to call that overfitting or not I suppose depends on your perspective.

I agree intuitive definitions are often murky, but given we are already throwing in murky notions of intention that are implicit in the word "target", I think an at least colloquial usage of overfitting is appropriate.

Sometimes we try micro-models on broader domains than what we expect they will work for, and they work fine. Sometimes not. The point is that the target here is not well defined because we are just using them as annotation tools with some human supervision and not in a "typical" production environment.