The role of the sampling mechanism for Bayesian inference on symmetric
functions of a finite population is examined under partial design and
partial label information. A new definition of partial exchangeabilit
y is proposed, together with a corresponding property of the sampling
mechanism. These properties provide conditions under which certain sym
metries in priors or designs can protect against lack of symmetry in o
thers, in the sense of Scott & Smith (1973).