Understanding ordinal regression


This is a really simple question, but one for which the answer continues to elude me!
I understand that in a binary logit regression the resulting logit is the probability of an event occurring, defined as


However, in an ordinal logit, in which there are multiple categories for the dependent, what does this represent?

Specially I am struggling to understand how an ordinal IV would be interpreted as affecting the ordinal DV.

Any help or advice is welcome, I am familiar with linear regression and attempting to teach myself some more complex models!