This publication presents a mechanism-first taxonomy for analyzing system trajectories across three loci: (1) the model layer (behavior under nonstationarity, constraints, and optimization pressure), (2) the human oversight layer (how supervision degrades, stabilizes, or develops over time), and (3) the coupling layer (emergent dynamics that arise when model and overseer co-adapt). The framework is organized as a shared triadic architecture: destabilizing processes (drift/degradation), stabilizing processes (correction/recovery), and generative processes (development/progression). Each class is defined by an underlying mechanism and an expected measurement signature, supporting audit use, evaluation design, and governance diagnostics rather than performance benchmarking. The paper synthesizes established constructs from concept drift and dataset shift, proxy/metric pathologies (Goodhart/Campbell effects), robustness and hidden fragility, delayed feedback instability, modular fragmentation and sensemaking collapse, human supervisory control and automation bias, resilience engineering, and complex adaptive systems. A key contribution is treating “human-in-the-loop” as a trajectory-bearing supervisory subsystem rather than a binary safeguard category: the oversight layer itself can drift, recover, or develop, and its coupling with the system it supervises can either preserve corrective integrity or silently erode it. Ψ(x) = ∇ϕ(Σ𝕒ₙ(x, ΔE)) + ℛ(x) ⊕ ΔΣ(𝕒′) — C077UPTF1L3 Licensed CRHC v1.0