This document defines the canonical terminology of the Entropic Governance Framework (EGF).
Where a term defined herein differs from colloquial, political, or domain-specific usage, these definitions take precedence for EGF interpretation.
Examples are illustrative and non-exhaustive; they clarify scope without limiting future applicability.
A measure of irreversible disorder or loss of usable energy resulting from energy transformation.
Within EGF, entropy is treated as a physical constraint, not a metaphor. Entropy cannot be eliminated, only managed, displaced, or delayed.
Illustrative examples (non-exhaustive):
The capacity to perform work or effect change within a system.
In EGF, energy is treated as the substrate of action; social and economic abstractions are derivatives of energy transformation.
Illustrative examples (non-exhaustive):
Energy transfer that produces change in a system; in governance contexts, the effective conversion of energy into capability or outcomes.
Illustrative examples (non-exhaustive):
Any process by which energy is converted from one form to another in order to perform work.
Illustrative examples (non-exhaustive):
A measure of usefulness, reversibility, and entropic efficiency of an energy source or transformation.
Two actions consuming similar quantities of energy may have very different entropic costs due to differences in energy quality.
Illustrative examples (non-exhaustive):
The irreversible increase in entropy resulting from a specific energy transformation or sequence of transformations.
Entropic cost is the primary evaluative constraint within EGF (see EGF–A1).
Illustrative examples (non-exhaustive):
The degree to which a transformation or system change can be undone without disproportionate additional entropic cost.
Reversibility is not absolute; it is assessed relative to the system boundary and relevant timescale.
Illustrative examples (non-exhaustive):
The defined scope within which entropic costs, flows, and responsibilities are accounted for.
EGF requires boundaries to be explicit. Boundary selection can change apparent costs; therefore, boundary rationale should be legible and contestable.
Illustrative examples (non-exhaustive):
The temporal horizon over which entropic cost, sustainability, and optionality are evaluated.
EGF allows multiple timescales, but requires clarity about which timescale a claim refers to.
Illustrative examples (non-exhaustive):
The capacity of a system to maintain low net entropy growth across relevant timescales while preserving structural and functional integrity.
Within EGF, sustainability is a physical property, not a moral or political label.
Illustrative examples (non-exhaustive):
The ability of a system to continue operating within entropic limits without collapse or irreversible degradation.
Illustrative examples (non-exhaustive):
The capacity to absorb shocks and recover function without disproportionate loss of integrity or optionality.
Illustrative examples (non-exhaustive):
The preserved capacity of a system to support multiple viable future states.
Loss of optionality constitutes high entropic significance (see EGF–A1 Axiom 8).
Illustrative examples (non-exhaustive):
A condition where a system becomes difficult to change without high additional entropic cost, often due to path dependence or infrastructure commitments.
Illustrative examples (non-exhaustive):
The collective management of constraints, resources, and trade-offs under uncertainty.
In EGF, governance is primarily understood as constraint management (EGF–A1 Axiom 9).
Illustrative examples (non-exhaustive):
A mode of governance that explicitly recognises entropy as the ultimate limiting constraint on system viability and organises decision-making accordingly.
The process by which access to energy, resources, or capability is distributed among agents under constraint.
Illustrative examples (non-exhaustive):
The specific rules, institutions, or systems used to allocate access.
Illustrative examples (non-exhaustive):
A contextual indicator used to estimate or correlate with entropic cost when direct measurement is impractical.
EGF treats proxies as useful but non-foundational; proxies must not be confused with invariants.
Illustrative examples (non-exhaustive):
The conceptual layer responsible for estimating entropic costs and tracking system state, including uncertainty.
Illustrative examples (non-exhaustive):
The degree to which entropic costs, allocation logic, and responsibility chains are visible, traceable, and contestable.
Legibility is a viability requirement (EGF–A1 Axiom 10).
Illustrative examples (non-exhaustive):
The condition in which entropic trade-offs or allocation mechanisms are hidden, obscured, or non-auditable.
Illustrative examples (non-exhaustive):
Any entity capable of intentionally or unintentionally transforming energy and thereby contributing to entropy within a system.
Entropic agency does not require consciousness, intent, or moral awareness. What matters is causal influence on energy transformation.
Illustrative examples (non-exhaustive):
An artificial system that performs goal-directed behaviour affecting resource use, allocation decisions, or energy transformation.
Within EGF, AI agents are treated as entropic agents to the extent that they cause or mediate energy transformation.
Illustrative examples (non-exhaustive):
The obligation borne by an entropic agent in proportion to its capacity to influence energy transformation and system outcomes.
Responsibility accrues regardless of whether an agent directly consumes energy or indirectly causes transformation through incentives, policies, or control.
Illustrative examples (non-exhaustive):
The traceable set of agents whose combined actions, incentives, and controls produce an outcome and its entropic cost.
Illustrative examples (non-exhaustive):
Normative priorities used to weight allocation decisions where multiple physically viable options exist.
Values may influence allocation, but they do not override physical constraint (EGF–A1 Axiom 6).
Illustrative examples (non-exhaustive):
An explicit rule or mapping that translates values into prioritisation across competing claims under constraint.
EGF prefers explicit weighting functions over implicit moralisation; explicitness enables contestation and legitimacy.
Illustrative examples (non-exhaustive):
The structured evaluation of values, responsibilities, and trade-offs in decision-making under constraint.
Ethics without constraint is unstable; constraint without ethics is illegitimate.
Illustrative examples (non-exhaustive):
A classification or membership construct used by a system to assign rights, duties, or access conditions.
EGF does not prescribe which identities are valid. It requires that identity’s role in allocation be legible, contestable, and bounded by constraint.
Illustrative examples (non-exhaustive):
A predictable pattern of systemic breakdown arising from misalignment with physical constraint or governance design.
See EGF–A3 for an informative treatment of several failure modes.
Illustrative examples (non-exhaustive):
The condition in which decision-making ignores cumulative irreversible loss, leading to deferred collapse.
Illustrative examples (non-exhaustive):
A cost (including entropic cost) imposed on other agents or future states without being represented in the allocating mechanism.
Illustrative examples (non-exhaustive):
A publicly articulated, non-proprietary framework intended to serve as a stable point of reference for interpretation and extension.
Illustrative examples (non-exhaustive):
A formally designated text that defines or constrains interpretation of the Entropic Governance Framework.
Illustrative examples (non-exhaustive):
Defining mandatory constraints or requirements within EGF.
Illustrative examples (non-exhaustive):
Descriptive or explanatory material that does not introduce binding constraints.
Illustrative examples (non-exhaustive):
A declared state of a document at a specific publication point, intended to be stable and citable.
EGF uses stable filenames and embeds version information within documents. Revisions should be explicit and traceable.
Illustrative examples (non-exhaustive):
This glossary is intended to remain conceptually stable even as measurement techniques, technologies, and institutional forms evolve.
Where ambiguity arises, interpretation should defer to: