Recognition, Consent, and Democratic Drift

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Authors: J. E. Fröderberg
Cited by: 2

Abstract

This preprint presents a formal, non-empirical diagnostic analysis of democratic legitimacy under contemporary conditions. It argues that populism persists not primarily because of misinformation or institutional design failure, but because it supplies recognition and alignment where institutional politics increasingly fails to do so. When political elites respond to this environment through proceduralism, moral condemnation, or reactive signal-following, democratic systems enter a self-reinforcing feedback loop of volatility, institutional hollowing, and legitimacy drift. The paper proceeds axiomatically, specifying minimal premises concerning consent, elections, and recognition, and deriving operational principles that constrain how democratic legitimacy can plausibly be renewed. It does not advance causal explanations, empirical tests, or normative prescriptions. Instead, it offers a formal diagnostic framework intended to clarify which stabilisation strategies are structurally insufficient once recognition scarcity and reactive leadership dominate political competition. An appendix explains how to read an AST-structured paper, and a second appendix provides a stylised, non-empirical illustration of how the derived output layer may be used diagnostically. Methodological note This paper employs an axiomatic and synthetic methodology (Axiomatic and Synthetic Theory, AST). The argument is self-contained and does not rely on external datasets, case studies, or methodological corpora for validity. For general methodological context, the AST master corpus is available at https://doi.org/10.5281/zenodo.18006746. Status Preprint — Version 1.1. Distributed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).

Fields of Study & Subjects

Populism Right-Wing Movements Political Conflict and Governance Qualitative Comparative Analysis Research

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
7 January 2026
Language
EN
Document type
Preprint