Modelling Civilizational Bifurcations Under Growing Governance Complexity

This repository contains a methodological white paper and accompanying numerical experiments presenting a unified framework for analyzing civilizational and systemic regime transitions as probabilistic outcomes of growing complexity and governance constraints. The framework combines a minimal analytical core inspired by World3-type system dynamics with a structurally rich model incorporating energy, food, information, governance, and technology subsystems. Regime transitions are modeled not as deterministic collapses or threshold events, but as stochastic realizations governed by an endogenous hazard process that evolves with system state. A central contribution of the work is the explicit separation between: structural vulnerability (pressure accumulation, complexity growth, governance overload), and event realization (the contingent timing of regime transitions). This separation enables counterfactual analysis, survival-based risk estimation, and comparison of alternative stress pathways without scripting outcomes. The modeling approach integrates: nonlinear system dynamics, probabilistic regime switching via hazard functions, Monte Carlo simulation for risk and timing distributions, and an integrative diagnostic indicator (IEKV) used strictly for interpretation rather than control. The framework is validated on stylized historical cases (e.g., mid-20th century Cuba and early-20th century Russia) and extended to a contemporary structural model with multiple interacting subsystems. Numerical experiments demonstrate that regime transitions may occur endogenously even in the absence of exogenous shocks, while structured shock sequences primarily alter the timing and concentration of risk rather than enforcing deterministic outcomes. The work is intended as a methodological contribution rather than a predictive tool. It does not provide point forecasts or policy prescriptions. Instead, it offers a structured way to reason about systemic vulnerability, complexity management, and regime transition risk under deep uncertainty. Potential application domains include long-term civilizational risk analysis, comparative political economy, stress testing of complex institutions, and the study of governance limits under accelerating technological and organizational complexity.