  We study how to incentivize agents in a target group to produce a higher
output in the context of incomplete information, by means of rank-order
allocation contests. We describe a symmetric Bayes--Nash equilibrium for
contests that have two types of rank-based prizes: prizes that are accessible
only to the agents in the target group; prizes that are accessible to everyone.
We also specialize this equilibrium characterization to two important
sub-cases: (i) contests that do not discriminate while awarding the prizes,
i.e., only have prizes that are accessible to everyone; (ii) contests that have
prize quotas for the groups, and each group can compete only for prizes in
their share. For these models, we also study the properties of the contest that
maximizes the expected total output by the agents in the target group.
