The Singularization Framework: Diagnosing Structural Fragility in Complex Adaptive Systems

This research monograph introduces the Singularization Framework, a theoretical model for diagnosing structural fragility in complex adaptive systems (CAS). Traditional explanations of systemic collapse frequently emphasize external shocks, entropy growth, or chaotic dynamics. In contrast, the present framework proposes that many complex systems fail due to structural over-compression, a condition in which optimization processes progressively reduce diversity, decentralization, and feedback permeability. Within this perspective, systemic collapse is interpreted as the outcome of a process called singularization: the concentration of decision authority, information flows, and resource allocation into increasingly narrow structures. While such concentration may initially increase efficiency, it simultaneously reduces adaptive capacity and resilience. The framework integrates three conceptual components. First, the Mallinckrodt Cycle models the dynamic lifecycle of complex systems as an oscillation between phases of exploration, optimization, structural compression, and eventual fragility. Second, the Compression–Resonance–Tension Index (CRTI) is introduced as a diagnostic expression for systemic fragility: CRTI = (C * T) / (R + epsilon) where C represents structural compression, R represents systemic resonance (the ability of the system to integrate external feedback), and T represents accumulated systemic tension. High CRTI values indicate increasing fragility and a higher probability of abrupt structural breakdown. Third, the concept of Strategic Reserve is introduced as a design principle for resilient systems. Strategic reserves consist of structural redundancy, cognitive diversity, and modular decentralization. Although these elements may appear inefficient during stable periods, they provide essential buffers that allow systems to absorb shocks and maintain adaptive capacity. The Singularization Framework connects ideas from cybernetics, network science, resilience theory, and complexity research. By combining structural network metrics, semantic entropy indicators, and nonlinear time-series signals, the model outlines possible empirical pathways for identifying early warning signs of systemic fragility across multiple domains, including financial systems, technological infrastructures, organizations, and geopolitical systems. Rather than offering deterministic predictions of collapse, the framework provides a diagnostic lens for understanding how structural optimization may gradually transform efficiency into fragility. The monograph is intended as an open theoretical contribution designed to stimulate interdisciplinary discussion and further empirical investigation within the field of complex systems science. Keywords für Zenodo complex systems complex adaptive systems system fragility resilience cybernetics network science system collapse structural compression CRTI Singularization Framework