  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.
