First post explores what Computational Macrohistory is (and isn't):
galenfontaise.substack.com/p/what-is-co...

If you're interested in evidence-based approaches to social dynamics, I'd love your thoughts.

#ComplexSystems #DataScience #QuantitativeSocialScience #Research

How:
Mathematical modeling, statistical analysis, complexity science, historical databases—all with rigorous validation and transparent uncertainty.
Current focus:
Arab Spring case study. Could we predict which countries would experience revolution in 2010-12 based only on structural conditions?

I'm excited to launch CMH Bulletin—a new project applying quantitative methods to understand large-scale historical dynamics.

What we study:
- Revolutions and political instability
- Economic cycles - crises
- Demographic pressures - social change
- Patterns in the rise - fall of civilizations

If you're into quantitative history, complex systems, cliodynamics, or simply understanding why societies collapse — glad to have you here.

-Galen Fontaise

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I'll post research updates, methodological reflections & findings here.
For more:
📰 Substack → galenfontaise.substack.com
🔗 LinkedIn → www.linkedin.com/in/galenfont...
📄 Orcid → orcid.org/my-orcid?orc...

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The framework rests on 8 foundational axioms defining when historical systems become scientifically tractable.

Currently in empirical validation: Arab Spring 2010-2012 as proof-of-concept case study.

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CMH applies math, statistics & dynamical models to history to identify recurring patterns and compute probability distributions for critical socio-political events.

No deterministic forecasts — honest probabilities only.

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🧵 Hi Bluesky!

I'm Prof. Fontaise, founder of FICSS (Lugano) & creator of Computational Macrohistory (CMH) — a quantitative science of large-scale historical systems.

A short intro:

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