Consent-Theoretic Framework for Quantifying Legitimacy: Stakes, Voice, and Friction in Adversarial Governance

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Authors: Farzulla, Murad
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Abstract

Abstract This paper develops a unified analytical framework for measuring political legitimacy across heterogeneous governance domains. Building on insights from constitutional political economy, social choice theory, and institutional analysis, the framework establishes consent-holding as a structural necessity of collective action. Legitimacy is operationalized as stakes-weighted consent alignment α(d,t), while friction F(d,t) measures the deviation between outcomes and stakeholder preferences. Key Contributions Five axioms, five theorems: Formal framework bridging normative democratic theory and empirical prediction Historical validation: Suffrage expansion, abolition, labor rights, and platform governance examined with quantified α/F trajectories Computational validation: Monte Carlo (1000 runs) with Bayesian learning agents shows stakes-weighted DoCS achieves highest alignment (α = 0.872) with lowest friction (94.9% reduction) Consent vs competence resolved: Domain-specific approach shows both as complementary dimensions of institutional legitimacy V-Dem v15 empirical data: Five countries, 1789–2024, quantifying suffrage and abolition trajectories Scope 140-page monograph (v2.0.0), 5 Parts, 21 sections, 4 appendices. The most comprehensive paper in the portfolio. Working Paper DAI-2501. Links SSRN: SSRN:5918222 ASCRI: systems.ac/1/DAI-2501 Research Lab: Dissensus AI v2.0.1 (2026-07-11): Corrected build: the previously deposited v2.0.0 PDF was generated from a superseded draft carrying statistical diagnostics (Ljung-Box, Friedman, Nemenyi) that are absent from the v2.0.0 source and could not be substantiated. The deposit now matches the clean v2.0.0 source build (142pp). No other content changes.

Fields of Study & Subjects

Computational and Text Analysis Methods Ethics and Social Impacts of AI Populism Right-Wing Movements

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
11 July 2026
Document type
Preprint