Any mapping from states to signals induces a distribution over possible posteriors. For decision-making purposes, one is interested in parameters of those posteriors, such as their quartiles or whether they first-order stochastically dominate some given distribution. We show that a generalization of Gale’s demand theorem can be used to characterize which distributions over possible posteriors with the requisite properties can be generated by some mapping from states to signals.