The Smoothed Likelihood of Doctrinal Paradoxes

When aggregating logically interconnected judgments from $n$ agents, the result might be inconsistent with the logical connection. This inconsistency is known as the doctrinal paradox, which plays a central role in the field of judgment aggregation. Despite a large body of literature on the worst-case analysis of the doctrinal paradox, little is known about its likelihood under natural statistical models, except for a few i.i.d. distributions [List, 2005]. In this paper, we characterize the likelihood of the doctrinal paradox under a much more general and realistic model called the smoothed social choice framework [Xia, 2020b], where agents' ground truth judgments are arbitrarily correlated while the noises are independent. Our main theorem states that under mild conditions, the smoothed likelihood of the doctrinal paradox is either $0$, $\exp(-\Theta(n))$, $\Theta(n^{-1/2})$ or $\Theta(1)$. This not only answers open questions by List [2005] for i.i.d. distributions but also draws clear lines between situations with frequent and with vanishing paradoxes.