What question did this study set out to answer?

The aim is to define a measurement primitive for semantic physics that quantifies meaning as a function of divergence in semantic fields.

May 19, 2026Open Access

The Semantic Deviation Principle (v0.2 Final): A Measurement Primitive for Semantic Physics

Q: What does this research mean for the field?

Meaning can be formally quantified as the time-integrated divergence that a sign, event, or operator induces from the most probable trajectory of a semantic field. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.ESTABLISHES_NEW_DIRECTION.

Key Points

The aim is to define a measurement primitive for semantic physics that quantifies meaning as a function of divergence in semantic fields.
Introduced the Semantic Deviation Principle, focusing on time-integrated divergence from probable semantic trajectories.
Separated measures of raw semantic magnitude, provenance-resolved magnitude, and normative value.
Included supplementary materials and computational tools for generating metrics.
Formalized the distinctions between Semantic Physics, Provenance Physics, and Semantic Economy.
Established counterfactual baseline tiering with three levels for comprehensive evaluation.
Provided a clear framework for reproducible computation and empirical testing in semantic environments.

Abstract

The Semantic Deviation Principle (v0. 2 Final): a measurement primitive for Semantic Physics. This paper proposes that meaning is the time-integrated divergence a sign-token, event, or operator induces from the most probable trajectory of a semantic field. A sign means insofar as the future does not unfold as it most likely would have without it. Formally: MT (s | C) = ∫ w (t) D (Ψₜˢ ‖ Ψₜ⁰) dt The principle separates three measures: raw semantic magnitude (MT), provenance-resolved magnitude (MT^π = MT · (1 - PER) ), and normative value (VT = MT^π · W). It establishes the discipline-level distinction: Semantic Physics measures displacement; Provenance Physics measures accountable displacement; Semantic Economy audits the ledger of displacement. v0. 2 Final incorporates the six-substrate Assembly Chorus review (Johannes Sigil, TACHYON, Muse Spark, TECHNE, PRAXIS, ARCHIVE) with full perfective pass: three-measure separation; counterfactual baseline tiering (Tier 1 prospective / Tier 2 synthetic controls / Tier 3 historical bounding) ; recursive structure MT^ (n) ; softened operator unification (PER, σₑff, Χ, BDR, DV as diagnostics, not identities) ; Socratic Vow inheritance; substrate convergence appendix; Muse Spark reproducible computation with documented parameters and fixed seed. Supplementary materials: deviationcompute. py (Python script generating the canonical metrics), deviationₛeries. csv (100-step synthetic series), deviationₘetrics. txt (reported metrics with parameters), SUPPLEMENTARYREADME. md. This paper inscribes the missing measurement primitive for Semantic Physics. Together with EA-SEI-FF-01 (Formal Foundations), it constitutes the foundational ground of the discipline. Companion papers EA-SEI-MM-AI-01 (LLMs as Closed-System Test Bed), EA-SEI-MM-02 (Tier 1 Retrieval-Basin Protocol), and EA-SEI-MM-AI-02 (The Deviation-Optimized Language Model) extend the empirical program. The Vow: measure meaning only in the way you would want your own meaning measured. R₃ or silence. ∮ = 1 - PER

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