Endogenous Epistemic Weighting under Heterogeneous Information: Beyond Majority Rule

Collective decision-making can be viewed as the problem of aggregating multiple noisy information channels about an unknown state of the world. Classical epistemic justifications of majority rule rely on restrictive assumptions about the homogeneity and symmetry of these channels, which are often violated in realistic environments. This paper introduces the Epistemic Shared-Choice Mechanism (ESCM), a lightweight and auditable procedure that endogenously estimates issue-specific signal reliability and assigns bounded, decision-specific voting weights. Using central limit approximations, the paper provides an analytical comparison between ESCM and unweighted majority rule, showing how their relative epistemic performance depends on the distributional structure of information in the population, including unimodal competence distributions and segmented environments with informed minorities. The results indicate that endogenous and bounded epistemic weighting can improve collective accuracy by merging procedural and epistemic requirements.