Frequentism is as abused as "orthodox statistics", and in any event, tends to evoke a conception of people interested in direct inference: assigning a probability (based on observed relative frequencies) to outcomes. Frequentism in statistical inference, instead, refers to the use of error probabilities--based on sampling distributions-- in order to assess and control a method's capability to probe a given discrepancy or inferential flaw of interest. Thus, a more suitable name would be error probability statistics, or just error statistics. One infers, for example, that a statistical hypothesis or other claim is well warranted or severely tested just to the extent that the method was highly capable of detecting the flaw, and yet routinely produces results indicating the absence of a flaw. But the most central role of statistical method in the error statistical philosophy is to block inferences on a variety of grounds, e.g., that the method had little capacity to distinguish between various factors, biases, failing to give the assumptions of the models used a sufficiently hard time.

But the real reason I wrote is because the first few sentences of this post made me think that perhaps the professor was me! I'm glad to hear there are other female philosophers of science who are frequentists. yet it wasn't me, given the rest of the post.