Journal of Systems Thinking · Volume 5, Issue 1 · 2025-12-22
DSRP as Universal Ontology
The Structural Foundation of All Systems
Derek Cabrera
https://doi.org/10.54120/jost.v25i1.dc6sfas6
Abstract
Across the sciences, each discipline develops its own domain ontology—its structural assumptions about what exists, from particles and fields to molecules, cells, minds, and social agents. Yet beneath this disciplinary diversity lies a deeper unity. This paper presents an empirically grounded structural ontology showing that the universe organizes itself through four Simple Interaction Rules (SIRs): Distinctions, Systems, Relationships, and Perspectives (DSRP). Using the Unified Calculus of Organization, we show that these operators are not independent categories but projections of one generative polarity expressed through eight elemental roles and three universal dynamics (4–8–3). These structures appear empirically in quantum state boundaries, molecular bonding symmetries, cellular architectures, ecological networks, social systems, and human cognition. They constitute the structural grammar of reality. Two lines of scientific evidence support this claim. First, existence evidence demonstrates that the DSRP invariants—polarity, part–whole recursion, relational interaction, and perspectival orientation—are instantiated in nature independent of human observers. Second, effect evidence shows that human cognition uses the same invariants but with measurable structural bias. When these biases are corrected, individuals exhibit large and replicable gains in systems thinking, metacognition, causal reasoning, and model accuracy. In an age dominated by large language models, this structural ontology becomes more than a philosophical insight—it becomes a practical necessity. Current LLM-based AI systems lack internal ontology: they do not represent boundaries, part–whole structure, causal or conceptual relationships, or perspectives. As a result, they hallucinate, contradict themselves, collapse distinctions, fabricate causal chains, and drift semantically over time. Without structure, there is no coherence. By formalizing the generative grammar of reality and cognition, the ontology advanced here provides the missing structural foundation that both humans and AI systems require to think, model, and understand reliably. It clarifies why humans reason the way they do, why AI systems fail the way they do, and why a shared structural framework—one that makes thinking visible, measurable, and governable—is essential for science, education, and human–AI intelligence. DSRP is not a theory of systems; it is the structural ontology that makes systems possible—and the generative grammar future human and artificial intelligence will require.
© 2025 Journal of Systems Thinking (JoST) · CC BY-NC-ND 4.0
