The Coercivity Law of Enaction Within Fisher-Generative Informational Realism: A Cybernetic Threshold for Autopoietic Closure

When does a complex adaptive system (CAS) (like a thermostat, a market, a flock, or a large language model) become a complex adaptive autopoietic system (CAAS), one that actively produces and sustains itself rather than merely adapting to its environment? We argue that this transition requires two simultaneous conditions. The first, established in a companion work, is architectural sufficiency. The system’s decision structure must achieve recursive closure at the third cybernetic order, the so-called fractal-seed point. The second, derived here, is corporeal viability. The system must pay a structural cost (the enactment tension E) large enough to hold its organization in place against perturbation. Working within Fisher-Generative Informational Realism (FGIR), an informational-realist framework in which information, not matter or energy, is the primary generative substrate of reality, we derive a scalar invariant E = Ipc2, where Ip is the integrated informational potential of the operative field and c is the global coherence conductance at which informational structure locks into place. This invariant marks the threshold at which a proto-autopoietic system crosses into full autopoiesis. Because FGIR treats physical mass-energy as the result of a freezing projection acting on an incorporeal informational manifold rather than as the foundation of reality, the same invariant that governs autopoietic closure in social and organizational systems also projects, under appropriate bridge conditions, for instance, onto the classical physical law E^=m^ c^2, or in a quantum context, the Schrödinger equation. The physical projection is stated as a conditional equivalence (T-BRIDGE), but it is not the focus of this paper. Rather, the central contribution is the cybernetic threshold itself and its operationalization. We show how a systems theorist can assess a system’s distance from critical admissibility, even when the absolute magnitudes of Ip and c are unavailable in domains that lack R(6) closure; we connect the coercivity threshold explicitly to Ashby’s Law of Requisite Variety, supplying the energetic constraint that Ashby’s purely combinatorial criterion leaves implicit. The contemporary case of large language models illustrates the framework. LLMs display transient, externally-scaffolded R(3)-like decision structure but fail the coercivity threshold, and so remain proto-autopoietic. The paper thus offers systems science a derived criterion, additional to architectural closure, for distinguishing full from proto-autopoiesis, with a specified but as yet unexecuted test program across physical, biological, cognitive, and social domains.