On the Degree of Generalizability of Condorcet Jury Theorem

The Condorcet jury theorem (CJT) is the probabilistic foundation that underlies jury decision-making and collective information aggregation at large. It has nonetheless been recognized that Condorcet's adoption of a statistically implausible premise – identical competence among all individuals – puts his seminal results in question, since jurors typically differ in their abilities. While many have attempted to generalize the CJT to juries consisting of heterogeneously competent individuals, we study the CJT in a more practical and policy-serviceable manner, exploring its degree of generalizability. Rather than stipulating probabilistic conditions for its validity to heterogeneous juries, as generalizations normally do, we run Monte Carlo simulations to find how often would unequally skillful jurors satisfy Condorcet's results, taking into account various jury sizes, and different values of mean competence and standard deviation. Our findings indicate that heterogeneous juries are typically consistent with, or perform very close to, Condorcet jurors