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1 November 2025 Preprint Consent Mechanics

Quantifying Legitimacy in Adversarial Environments

A Consent-Theoretic Framework

Murad Farzulla

Abstract

Political legitimacy formalized as stakes-weighted consent alignment (α), enabling systematic comparison across democratic, technocratic, and algorithmic governance systems. Computational validation via Monte Carlo demonstrates consent-based mechanisms achieve high alignment with substantive friction reduction, outperforming plutocratic and purely technocratic alternatives.

Suggested Citation

Murad Farzulla (2025). Quantifying Legitimacy in Adversarial Environments. Dissensus AI Working Paper DAI-2501. DOI: 10.2139/ssrn.5918222

Methodology

Monte Carlo simulation Bayesian learning Multi-agent systems

Topics

Political Economy Legitimacy Theory Adversarial Systems