> This increase in bias cannot be blamed merely on the data. This is debatable in this case. The grouped model might be a better fit to the data: it indicates

> This increase in bias cannot be blamed merely on the data. This is debatable in this case. The grouped model might be a better fit to the data: it indicates a higher bias in salaries at higher skill levels. It sounds completely plausible that the gender bias for unskilled workers is less than for high skilled workers. Models can be under-fit as well as over fit. Just using a dummy variable for gender might not properly capture interactions like this. But of course it’s always possible that this is just an artefact of the training data.