Contemporary societies are often "polarized", in the sense that sub-groups within these societies hold stably opposing beliefs, even when there is a fact of the matter. Extant models of polarization do not capture the idea that some beliefs are true and others false. Here we present a model, based on the network epistemology framework of Bala and Goyal ["Learning from neighbors", \textit{Rev. Econ. Stud.} \textbf{65}(3), 784-811 (1998)], in which polarization emerges even though agents gather evidence about their beliefs, and true belief yields a pay-off advantage. The key mechanism that generates polarization involves treating evidence generated by other agents as uncertain when their beliefs are relatively different from one's own.