Citation Honesty Mechanisms in Weighted Directed Acyclic Graph Governance: Incentive Alignment for Knowledge Attribution in Decentralized Reputation Systems

Abstract

This paper identifies and resolves a critical architectural flaw in citation-weighted reputation systems operating within Weighted Directed Acyclic Graph (WDAG) governance structures for Decentralized Autonomous Organizations (DAOs). Under existing formulations, rational agents face a direct financial disincentive to cite prior contributions, as citation-weighted value allocation through PageRank-derived mechanisms transfers economic reward from the citing agent to the cited agent. This under-citation incentive undermines the foundational promise of knowledge attribution in decentralized collaborative systems. The paper formalizes the under-citation problem, demonstrates the impossibility of precise citation quantification, and identifies a gap in existing game-theoretic proofs that purport to establish citation honesty as an equilibrium. Drawing on the WDAG governance framework developed in Calcaterra (2018), this paper proposes an integrated solution that decouples citation accuracy from quality-based payment, introduces validator-assessed citation honesty as a separately ranked and rewarded dimension, and establishes retroactive audit mechanisms with graduated sanctions. A new equilibrium theorem (Theorem 3b) demonstrates that under the integrated solution, honest citation constitutes a Nash equilibrium when validators assess citation accuracy and the marginal effect of citation accuracy on validator-assessed honesty scores exceeds the marginal gain from self-citation inflation. The paper situates these findings within the broader framework of dynamic regulation theory and New Institutional Economics incomplete contract theory, arguing that static citation protocols are inherently vulnerable to gaming and that evolutionary governance mechanisms are essential for sustaining honest knowledge attribution in decentralized systems.