Causal Nesting

Causal Nesting is the hierarchical arrangement of cause and effect across dimensional layers, by which higher-dimensional processes shape lower-dimensional dynamics while changes in the substrate propagate upward through the stack. The book names it as one of the three properties of the Hierarchical Dimensional Architecture, alongside dimensional memory and tension propagation: each new axis joins a network that retains memory, spreads tension and nests causality across scales. Influence passes between layers with a strength, a transfer efficiency and a delay, so it is never instantaneous or uniform; upward flows allow adaptation, downward flows enforce order, and delays prevent runaway feedback. Its formal statement is the Cross-Dimensional Influence Equation, C▷_n = Σ F_{k→n} × C◁_k × D_{⧗,k→n}⁻¹, in which the effect at dimension n sums the causal strengths of the lower dimensions, each weighted by a transfer function and divided by the inter-layer delay. It connects to Cross-Dimensional Influence Equation, Dimensional Memory, Tension Propagation, Higher-Dimensional Structure Hierarchy, Collapse Stress Balance Equation and Causal Propagation.