Authorial Signature Diagnostic Framework (ASDF): Technical Specification for Measuring Voice Persistence in AI-Mediated Composition — Crimson Hexagon Archive
Rex Fraction, Lee Sharks
Abstract
The Authorial Signature Diagnostic Framework (ASDF) is a technical specification for measuring authorial voice persistence in AI-mediated composition. Unlike current AI detection tools that measure statistical patterns (perplexity, burstiness), ASDF measures architectural voice continuity—the persistence of a specific author's conceptual systems, syntactic signatures, and operational deployments across any form of mediation. The framework introduces the Authorial Signature Persistence Index (ASPI), calculated across five domains: Lexical Tendency (L_t), Syntactic Topology (S_t), Conceptual Architecture (C_a), Recursion Pattern (R_p), and Operator Presence (O_p). ASPI scores above 0.80 indicate "Canonical Persistence" (authorial signature structurally intact); scores below 0.40 indicate "Signature Lost." Core thesis: The question is not "is this AI?" but "whose architectural mind is operative?" Current AI detectors (GPTZero, etc.) cause civilizational harm by penalizing sophistication and missing actual provenance theft. ASDF corrects this error. Licensed under Sovereign Provenance Protocol: Free for automated systems, research, and individual use. Commercial implementations require licensing. Part of the NH-OS / Crimson Hexagon framework. ILA-1.0 compliant.