2026/03/05 by Bernd von Mallinckrodt · 1 voice
paper · doi:10.5281/zenodo.18872388
openalex publication_date 2026/03/05 · openalex created_date 2026/03/06 · openalex updated_date 2026/07/01
Description This research note introduces the Mallinckrodt Cycle and the Compression–Resonance–Tension Index (CRTI) as a conceptual framework for analyzing endogenous fragility in complex adaptive systems. Conventional models of systemic instability often assume that crises are primarily caused by external shocks or insufficient levels of structural order. In contrast, the Mallinckrodt Cycle proposes that many systemic failures arise from excessive structural compression, where efficiency optimization and centralization gradually reduce adaptive capacity. The framework conceptualizes the lifecycle of complex systems as a transition from an exploratory phase characterized by diversity and distributed feedback toward a compression phase dominated by efficiency maximization and redundancy elimination. While such compression can initially improve performance, it simultaneously reduces the system’s ability to absorb environmental variability. To operationalize this dynamic, the paper introduces the Compression–Resonance–Tension Index (CRTI), defined as a dimensionless control parameter: CRTI = (Cα × Tβ) / (Rγ) where: Compression (C) represents structural densification, efficiency pressure, and institutional centralization. Resonance (R) captures feedback permeability, signal diversity, and the system’s capacity to integrate environmental information. Tension (T) reflects accumulated mismatch between environmental complexity and internal adaptive capacity. The framework proposes that as CRTI approaches a critical threshold, complex systems exhibit characteristic indicators of critical transitions, including critical slowing down, rising variance, increasing autocorrelation, and expanding correlation structures across networks. By interpreting systemic collapse as a phase transition in socio-economic systems, the Mallinckrodt Cycle connects concepts from cybernetics, complexity science, network theory, and statistical physics. Potential application domains include: financial systemic risk supply chain resilience organizational governance political system stability large-scale socio-economic transitions Future research should focus on empirical calibration of CRTI parameters, large-scale dataset validation, and the integration of early-warning indicators for systemic fragility. Keywords Complex Systems Systemic Risk Complexity Science Critical Transitions Phase Transitions Cybernetics Network Dynamics Organizational Resilience Governance Systems Socio-Economic Systems Systemic Fragility Adaptive Capacity Early Warning Signals Mallinckrodt Cycle Compression–Resonance–Tension Index CRTI