The Representation Stack: A Reference Model for How Reality Becomes Measurable, Represented, Optimized, and Interpreted

The Representation Stack is a structural model explaining how an underlying condition becomes something a system can measure, compare, represent, optimize, and interpret. It traces five representational layers: measurement, metrics, operational representation, optimization, and narrative.For each layer, the model identifies its function, what it preserves, what it loses, the substitution it introduces, and its characteristic form of failure. It also explains how filtering, compression, representation substitution, proxy optimization, constraint weakening, coherence stabilization, feedback weakening, and recursive reuse can transform ordinary representation into self-reinforcing misalignment.The document includes a backward diagnostic method for tracing consequential decisions from narratives, targets, dashboards, or model outputs back toward their ground conditions. Within the wider Reality Drift framework, the Representation Stack explains how systems can remain coherent and operational while losing corrective contact with what their representations were built to track, preserve, or improve.