Event

Understanding Democratisation and Civil War with Statistical Physics

12 - 14 March 2025
2:00 pm - 6:00 pm

Location

Complexity Science Hub
Complexity Science Hub, Metternichgasse 8, 1030 Vienna

Organizer

Complexity Science Hub
Email
events@csh.ac.at

Organizer(s)

  • Attendance: on site
  • Language: EN

Event

Understanding Democratisation and Civil War with Statistical Physics

Uncertainty persists over how and why some countries become democratic and others do not or why some remain democratic and others ‘backslide’ toward autocracy. Furthermore, while scholars generally agree on the nature of ‘democracy’ and ‘autocracy’, the nature of regimes in between—and changes between them—are much less clear.

A clearer understanding of these processes is not purely academic. Several studies suggest that regimes in the middle range — between full autocracies and full democracies — are most prone to war, so there is an inverted U relationship between democratic proximity and conflict risk. The empirical support of such studies is relatively mixed or disputed, presenting an area of research to which an interdisciplinary approach combining statistical physics and political science may help clarify.

The workshop will explore the use of statistical physics for modeling civil conflict in its political and environmental context by bringing together several key researchers in relevant areas. Nina von Uexkull studies the relationship between civil conflict and climate change. Håvrad Hegre’s research revolves around how democratic institutions can prevent armed conflict and how to forecast political events such as armed conflict. Roman Hoffmann from IIASA studies the relationship between climate change and population dynamics the underlying causes and consequences of different types of migration. CSH postdoc Eddie Lee develops multi-scale models of conflict spread borrowing on techniques from statistical mechanics and information theory.

We will address the following: (1) how to reframe the relationship between democracy and conflict risk in terms of regime dynamics, (2) identify causal mechanisms for conflict risk in the presence or absence of democratization or automatization with the help of physics-based models, (3) explore the interplay between climate change, democratization, and conflict risk and potential modeling approaches.

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