Propositions of Commitment Theory: A Research Prospectus
Year: 2026
Type: preprint
Abstract: This deposit is P-000, the founding document of Commitment Theory (CT) — the framework within which the empirically supported Conservation Law of Commitment operates. The prospectus establishes the theory's definitions, primitives, axioms, propositions, and research program. CT formalizes the commitment kernel as the minimal identity-preserving deontic invariant of a signal — the obligations, prohibitions, permissions, and modal constraints that must survive transformation for semantic continuity. Two laws structure the theory: a First Law (commitment is conserved under governed transformation, C(T_gov(S)) = C(S)) and a Second Law (under ungoverned transformation, the kernel decays monotonically with cumulative entropy scaling as Ω(σ√n)). The McHenry Axioms — Compression Precedes Ignition, Lineage Resilience, Input-Response Fidelity, the Blackhole Law, and the Lineage Custody Clause — provide the constitutional foundation, operationalized through a six-gate governance protocol and the MO§E§™ enforcement architecture. The prospectus introduces nine novel terms verified against Google Scholar, Scopus, arXiv, ACL Anthology, PhilPapers, SSRN, and IEEE Xplore (April 15, 2026) as occupying clean conceptual whitespace. It disambiguates CT's usage of "commitment" from five adjacent academic traditions: philosophy of language (Brandom, Walton & Krabbe), NLP epistemic stance (CommitmentBank), cryptographic protocols (Blum, ABBA), organizational psychology (Meyer & Allen), and Conservation of Resources theory (Hobfoll). It outlines a five-paper empirical research agenda extending the theory across semantic entropy rate, compression-fidelity bounds, governance density, cross-system fidelity, and metrology of C(S). The Conservation Law of Commitment — the law within the theory — is deposited separately at DOI 10.5281/zenodo.20029607 and is referenced throughout this prospectus. The framework is offered as a falsifiable, operational system; the research community is invited to replicate, falsify, extend, and apply the propositions.
Author: McHenry, Deric J
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7160307854
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