Quick question, is ordinal logistic regression a linear or nonlinear model? Finding different sources supporting the other, and the more I read the more I get confused myself.
Perse, it should fall under GLM, as logit does. Or?
All ordinal regression models in use are nonlinear because they are anchored to a probability scale and regression effects must bend to keep probabilities within [0,1]. You could say that the cumulative probability model class of ordinal regression (proportional odds, proportional hazards, probit) falls under GLM, though most people's concept of GLM includes only one intercept and cumulative probability models have $k-1$ intercepts for $k$ distinct values of $Y$. The software needed to fit ordinal models is specialized and is not handled by GLM software, because of the multiple intercepts. Some resources are at https://fharrell.com/post/rpo.