The bayesian/frequentist distinction can cover three different things that may occasionally be mixed up:

• The core philosophical disagreement (the "proper" one) about whether probabilities an agent's knowledge / uncertainty about the world, or whether they represent frequencies of some event. For example, a frequentist in this sense might say that it's meaningless to talk about the probability that the millionth binary digit of pi is even or odd. I think frequentist epistemology is mostly discredited, but that it used to be dominant.

• There are a bunch of hodge-podge statistical methods and tests (like p-values); and later on attempts to unify everything in terms of bayesian methods. People used to the "old" methods may not particularly call themselves "frequentists" or care that much about such labels; those pushing for the new (better) methods are the ones stressing the distinction (hunting down the sin of frequentism), sometimes to the annoyance of the rest.

• Thinking in probabilities versus thinking in frequencies (80 women out of a hundred); the human brain works better when a problem is presented in terms of frequencies