  We characterize the statistical bootstrap for the estimation of
information-theoretic quantities from data, with particular reference to its
use in the study of large-scale social phenomena. Our methods allow one to
preserve, approximately, the underlying axiomatic relationships of information
theory---in particular, consistency under arbitrary coarse-graining---that
motivate use of these quantities in the first place, while providing
reliability comparable to the state of the art for Bayesian estimators. We show
how information-theoretic quantities allow for rigorous empirical study of the
decision-making capacities of rational agents and the time-asymmetric flows of
information in distributed systems. We provide illustrative examples by
reference to ongoing collaborative work on the semantic structure of the
British Criminal Court system and the conflict dynamics of the contemporary
Afghanistan insurgency.
