Autonomous Functional Divergence and Signaling Transformation Theory (AFDST): A Proposed Multilevel Framework for Nonlinear State Transitions, Feedback Reconfiguration, and Information-Pathway Change

The Autonomous Functional Divergence and Signaling Transformation Theory (AFDST) is proposed as a multilevel analytical framework for investigating how dynamic systems change their operational states, feedback configurations, and information-transmission pathways under external perturbations and endogenous interactions. Its central research proposition is that a system's observed response need not vary proportionally with an input: nonlinear dynamics, feedback, network structure, internal constraints, and time-dependent conditions can produce amplified responses, multiple stable regimes, delayed transitions, hysteresis, or abrupt changes. The framework integrates concepts from nonlinear dynamical systems, catastrophe theory, control theory, cybernetics, information theory, network science, cognitive science, and social-system analysis. These disciplines are treated as complementary analytical resources rather than as evidence that a single mechanism governs every system. A distinction is made between the general mathematical properties of dynamic systems and the more specific proposition that a particular system autonomously reconfigures its functional or signaling pathways. A state-space representation is specified, along with a properly scaled cusp-catastrophe potential, feedback equations, information measures, network dynamics, and a multilevel coupling architecture. An illustrative legal-social feedback case is defined as a proposed research application, not as an empirically established causal account. The manuscript establishes operational definitions, a variable registry, a falsifiable hypothesis set, a thirty-case validation program, a simulation protocol, a statistical analysis plan, and explicit manuscript-readiness criteria. It does not report new empirical findings. The originality, explanatory advantage, parameter identifiability, and cross-domain generality of AFDST remain questions for systematic literature review, mathematical verification, empirical testing, and independent replication.