I did not perceive your comment as anti-bayesian, or at least not necessarily so! :)

But are you sure you know what I meant when I said “uninformative prior”? Because choosing an uninformative prior does not involve choosing any parameters: there is only one uninformative prior, and it’s the constant (flat) distribution which assigns equal probability to every value. It encodes no information and does not bias the posterior or result. It is the one and only mathematically-neutral prior. You can think of it as being a bit like an “identity function”.