Evolutionary Gap Theory (EGT): A Unified Framework for Analyzing, Measuring, and Predicting the Dynamics of Complex Systems

The Evolutionary Gap Theory (EGT) presents an analytical-quantitative framework for identifying, measuring, and predicting the consequences of dynamic misalignment between two fundamental functions of complex systems: the capacity for purposive change (Capability) and the capacity for feedback-driven course correction (Guidance). By defining the latent variable "Evolutionary Gap" as the net rate of misalignment between these two functions, and by providing the GEGI as an operational measurement tool, EGT demonstrates that the widening of this gap systematically undermines a system's ability to recognize its own safe operating boundaries. Through three causal channels—cognitive delay, diminished regulatory power, and increased forecast error—this gap translates into escalating systemic pressure. Empirical findings from panel data across 50 countries (2000–2023) reveal that GEGI predicts planetary stress with an R² of 0.612, outperforming competing models (GDP, Governance, HDI, EKC, STIRPAT). Four testable propositions are derived from the theory; three are confirmed by available data, with one pending future investigation. The theory's core innovation lies in its generalizability across seven levels of analysis—from the cellular to the civilizational—and its foundation upon three independent proofs drawn from control theory, thermodynamics, and catastrophe theory. EGT does not claim that this gap is the sole driver of crises, but rather posits it as one of the fundamental, recurring mechanisms in the history of complex systems, previously unmodeled in quantitative and systematic terms.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-07-30
DOI
https://doi.org/10.5281/zenodo.21710093
Primary Topic
Complex Systems and Decision Making
Type
article
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article

Evolutionary Gap Theory (EGT): A Unified Framework for Analyzing, Measuring, and Predicting the Dynamics of Complex Systems

Mobina Alizadeh, Vahid Alipour
Zenodo (CERN European Organization for Nuclear Research)
Complex Systems and Decision Making
article

Evolutionary Gap Theory (EGT): A Unified Framework for Analyzing, Measuring, and Predicting the Dynamics of Complex Systems

Mobina Alizadeh, Vahid Alipour
article en

Abstract

The Evolutionary Gap Theory (EGT) presents an analytical-quantitative framework for identifying, measuring, and predicting the consequences of dynamic misalignment between two fundamental functions of complex systems: the capacity for purposive change (Capability) and the capacity for feedback-driven course correction (Guidance). By defining the latent variable "Evolutionary Gap" as the net rate of misalignment between these two functions, and by providing the GEGI as an operational measurement tool, EGT demonstrates that the widening of this gap systematically undermines a system's ability to recognize its own safe operating boundaries. Through three causal channels—cognitive delay, diminished regulatory power, and increased forecast error—this gap translates into escalating systemic pressure. Empirical findings from panel data across 50 countries (2000–2023) reveal that GEGI predicts planetary stress with an R² of 0.612, outperforming competing models (GDP, Governance, HDI, EKC, STIRPAT). Four testable propositions are derived from the theory; three are confirmed by available data, with one pending future investigation. The theory's core innovation lies in its generalizability across seven levels of analysis—from the cellular to the civilizational—and its foundation upon three independent proofs drawn from control theory, thermodynamics, and catastrophe theory. EGT does not claim that this gap is the sole driver of crises, but rather posits it as one of the fundamental, recurring mechanisms in the history of complex systems, previously unmodeled in quantitative and systematic terms.

Zenodo (CERN European Organization for Nuclear Research)
Decent work and economic growth
Openalex Percentile: Top 5%
Complex Systems and Decision Making
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