Large language models have been argued to refute the argument from the poverty of the stimulus based on islands because they acquire human-like generalizations regarding islands. I consider this argument and extend previous experimental work by introducing new controls for clausal embedding (i.e., directly comparing non-island embedded extraction vs. island extraction) and by analyzing suites of models with exposure to different quantities of data.