What's the "generalized Born rule". For me the Born rule is a postulate saying that for any state, represented by a statistical operator ##\hat{R}## the outcome of the measurement of an observable ##A## to be the value ##a##, represented by a self-adjoint operator ##\hat{A}## defining a (generalized) orthonormalized eigenvector basis ##|a,\beta \rangle## is given by
$$P_A(a|\hat{R})=\sum_{\beta} \langle a,\beta|\hat{R}|a,\beta \rangle,$$
where the sum can also be an integral or both a sum and an integral, depending on the specific spectral properties of ##\hat{A}##.
For me that's a postulate and nothing that can be derived. Weinberg has given a thorough analysis of whether the Born rule is derivable from the other postulates (all well hidden above ;-)) coming to the conclusion that it can't be derived. I don't need an assumption about what happens to the state of the system due to the interaction between the measured object and the measure device, and I can't give a general one, because of course it depends on the details of this device. For sure I don't need a collapse for formulate the Born rule. It simply tells me that I have to do the measurement on a large ensemble of equally stochastically independent prepared systems to check whether the prediction of the Born rule concerning the probabilities is correct or not (within a given significance according to standard statistical rules).