If you look at the history of statistics, you'll find plenty of practically motivated ad-hoc problem solving like "hmm, how do we get R^n to map onto [0,1]" Log

If you look at the history of statistics, you'll find plenty of practically motivated ad-hoc problem solving like "hmm, how do we get R^n to map onto [0,1]" Log odds were used long before logistic regression and GLMs came along, and it certainly doesn't sound backwards to me to try and explain how people came to use a technique that initially looks very arbitrary (why not model probabilities directly?)