Grammatical Governance Under Entropy

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Authors: Jamie Morris
Cited by: 0

Abstract

This work presents a conceptual, constraint-based framework for understanding aging, persistence, and the limits of natural selection through the lens of thermodynamics and systems governance. We introduce a grammatical model of persistence in which complex systems transition through distinct phase states—Noun, Horizon, Flag-Waving, and Verb—as entropy increases and the cost of global coordination rises. In this framework, “nounhood” represents enforceable identity and repairable coherence, while “verbhood” represents resolution into transient processes. Using abstract constraint simulations, the analysis identifies an implied evolutionary equilibrium (~constraint level 1.4) that maximizes reproductive success while avoiding the energetic cost of extreme long-term persistence. This explains why biological evolution reliably produces finite lifespans and why additional investment in post-reproductive persistence yields diminishing evolutionary returns. The framework further shows that increasing constraints can significantly delay grammatical collapse by making dysfunction energetically expensive, without violating thermodynamic principles. Persistence is therefore reframed not as resistance to entropy, but as successful constraint negotiation within finite time horizons. This work is non-operational and non-interventional. It does not propose biological, medical, or technological implementations. Instead, it provides a unifying theoretical map connecting biology, information theory, thermodynamics, and systems governance, and clarifies why extending persistence beyond evolutionary limits would require deliberate informational governance rather than further optimization of natural selection.

Fields of Study & Subjects

Complex Systems and Dynamics Philosophy and History of Science Evolution and Genetic Dynamics

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
11 January 2026
Document type
Preprint