In brms, hypothesis() is, in part, a convenience function for combining posterior distributions. The problem identified in the original post is that we would expect the outputs of hypothesis and conditional_effects to be identical here, but they are not. I wonder if this is related to Ordinal Regression - conditional effects discrepancy?