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Abstract    The Core Models graphical system (Graphic Causality System), a formal language for mapping causal relationships through radial axes and directional vectors, has proven successful in unifying complex physiological concepts. This work extends its application to foundational negative feedback structures in economics, demonstrating a universal “grammar” for modeling homeostasis—the self-correcting processes that maintain system stability. By translating canonical economic balancing loops (e.g., infrastructure-wear-activity, resource-renewal) into this standardized visual language, we provide a novel didactic tool. The system's modular design, which scales from simple two-parameter loops to complex multi-axis integrations, reduces cognitive load and fosters pattern recognition. The most profound validation of this framework is its domain-agnostic nature: the same topological constructs model disparate systems, with only the parameter labels changing. This attempts to establish the Core Models system as a foundational step toward a “Rosetta Stone” for systems thinking, bridging disciplines by making the fundamental principles of circular causality visible and intuitively understandable. Keywords Economic Homeostasis, Negative Feedback, Core Models, Graphical System, Causal Diagrams, Systems Thinking, Economic Education, Universal Grammar, Cross-Disciplinary Modeling, Dynamic Equilibrium   

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