Governing the Unstable: State Resilience, Cognitive Warfare, and the Crisis of Democratic Governance in a Multipolar World

The 21st century is defined by a fundamental tension between the pursuit of stability and the inevitability of chaos. From the erosion of democratic norms to the rise of cognitive warfare and hybrid threats, states and international institutions face unprecedented challenges in governing an increasingly multipolar and unstable world.This Research Topic, inspired by the core theme of the CESRAN 2026 conference – the dialectic between stability and disorder – seeks to explore how democratic governance can survive and adapt in an age of information manipulation, cognitive operations, and systemic crises. It brings together cutting-edge research on state resilience, the weaponisation of disinformation, and the vulnerabilities of democratic institutions facing hybrid pressures.By bridging the conference’s focus on global instability with Frontiers in Political Science’s interest in hybrid threats and democratic resilience, this collection aims to provide theoretical and policy-relevant insights into how societies can defend their governance structures while navigating the complexities of a multipolar, cognitively contested environment.We welcome contributions that examine, among other topics:• Cognitive warfare as a threat to democratic decision‑making• State resilience strategies against disinformation and hybrid attacks• The crisis of democratic legitimacy in the face of systemic instability• Comparative perspectives on governing through chaos• Institutional responses to the weaponisation of informationThis Research Topic builds on the CESRAN 2026 (International Centre for Strategic Research and Analysis), which will take place in Budapest, Hungary, on 7-10 July 2026. Topic editors: Marco Marsili, Rahman DAG, Salome Dundua Source: https://www.frontiersin.org/research-topics/83238/governing-the-unstable-state-resilience-cognitive-warfare-and-the-crisis-of-democratic-governance-in-a-multipolar-world