Computational Macrohistory: A New Chapter

January 2026

Project Evolution

When I first launched this blog in 2019, Computational Macrohistory was a theoretical framework in its early stages—an attempt to formalize Peter Turchin’s cliodynamics with explicit axiomatic foundations and rigorous mathematical underpinning.

Six years later, the project has evolved significantly:

  • Theoretical refinement: The original 8 axioms (A1-A8) have been formalized with precise mathematical statements and operational definitions
  • Empirical focus: Moving from pure theory to concrete case studies (Arab Spring 2010-12, with more to follow)
  • Methodological rigor: Emphasis on falsifiable predictions, explicit uncertainty quantification, and transparent validation protocols
  • Community building: Engaging with researchers, data scientists, and analysts interested in quantitative approaches to macrohistory

Why Substack?

After careful consideration, I’ve decided to move primary content publication to Substack for several reasons:

1. Direct relationship with readers
Substack’s email-based model ensures that updates reach subscribers directly, rather than depending on algorithm-driven social media or sporadic blog visits.

2. Consistency and momentum
A weekly newsletter format creates accountability and rhythm—essential for building a research program incrementally and transparently.

3. Community engagement
Substack’s comment system and discussion features enable deeper engagement than traditional blog platforms.

4. Long-form friendly
The platform is optimized for the kind of in-depth, technical content that CMH requires (1500-3000 word posts exploring complex topics).

5. Future monetization
When the research reaches maturity (validated models, operational datasets, policy-relevant insights), a paid tier will enable sustainable development without institutional constraints.

What Happens to This Blog?

FICSS Institute (this site) remains the institutional home for Computational Macrohistory:

  • Foundational documents: The 8 axioms, theoretical framework, and formal papers will continue to live here
  • Research archive: Summaries of Substack posts will be cross-posted here for discoverability and institutional record
  • Resources: Datasets, code repositories (GitHub), and technical documentation will be linked from here
  • About/Contact: The “official” information hub

Substack becomes the active research blog:

  • Weekly posts: Ongoing research updates, case study development, methodological explorations
  • Series: Deep-dives into each axiom, empirical applications, validation results
  • Current analysis: Applying CMH frameworks to contemporary events (carefully, with explicit uncertainty)
  • Community: Discussion, feedback, collaboration opportunities

Where to Follow

Primary content (subscribe here):
📧 Computational Macrohistory Bulletin on Substack

Weekly posts exploring:

  • The 8 foundational axioms in depth
  • Arab Spring case study (2010-12): retrospective validation
  • Methodological development (Bayesian inference, Monte Carlo simulations, validation protocols)
  • Long-term: operational early-warning frameworks

Other channels:

  • 🔗 LinkedIn: www.linkedin.com/in/galenfontaise (professional updates, networking)
  • 💻 GitHub: github.com/ficss-institute (datasets, code, reproducibility)
  • 🌐 FICSS Institute: This site (institutional home, formal documentation)

Current Focus: The Axiom Series

Starting this month, I’m publishing a systematic series exploring each of the 8 foundational axioms:

A1 – Statistical Aggregation: Why individual chaos produces collective order
A2 – Historical Ergodicity: When is the past informative about the future?
A3 – Structural Causality: Events emerge from observable variables, not randomness
A4 – Continuous Dynamics: Modeling historical evolution as differential equations
A5 – Endogenous Indeterminacy: Why prediction is intrinsically probabilistic (chaos theory)
A6 – Limited Reflexivity: How predictions alter the system (and why that’s manageable)
A7 – Predictive Decay: Accuracy degrades exponentially with time horizon
A8 – Computational Falsifiability: Every model must generate testable predictions

Each axiom gets a dedicated post with:

  • Formal mathematical statement
  • Plain-English translation
  • Real-world examples
  • Implications for CMH
  • What breaks the axiom (edge cases, limitations)

What’s Changed Since 2019?

Theoretical:

  • Axioms now have rigorous mathematical formulations (not just conceptual)
  • Explicit treatment of uncertainty (Bayesian frameworks, Monte Carlo methods)
  • Integration of chaos theory and reflexivity (Lucas Critique addressed directly)

Empirical:

  • Shift from pure theory to validation-first approach
  • Arab Spring case study as proof-of-concept (testable, retrospective)
  • Focus on falsifiability: models that can be proven wrong

Methodological:

  • “Sloppiness as structure”: embracing uncertainty as feature, not bug
  • Emphasis on qualitative pattern recognition over precise quantitative forecasts
  • Transparent acknowledgment of what CMH CANNOT predict (black swans, individual actions, long-term specifics)

Ethical:

  • Explicit framework for responsible use (non-maleficence, transparency, no repressive applications)
  • Recognition of dual-use concerns (early warning ≠ social control)

Join the Journey

Computational Macrohistory is an ambitious, long-term research program. Progress is incremental, uncertain, and contingent on empirical validation at every step.

If you’re interested in:

  • Quantitative approaches to social science
  • Mathematical modeling of complex systems
  • The intersection of history, data science, and forecasting
  • Rigorous but accessible research done in public

Subscribe to the Substack: https://galenfontaise.substack.com

Weekly posts begin January 2026. First series: the 8 axioms explained.

Questions, feedback, or collaboration inquiries?
📧 Email: info@ficss.institute
💬 Substack comments (best for public discussion)
🔗 LinkedIn: https://www.linkedin.com/in/galenfontaise

Thank you for following this work. Onward.

— Galen Fontaise
Founder, FICSS Institute

Similar Posts