The Spiral Self-Sorter: A Motion-Based Convergence Tool for Post-Debate Decision Collapse

This preprint introduces the Spiral Self-Sorter (SSS), a minimal, motion-based decision tool designed to resolve stalemates after deliberation has surfaced assumptions and agreed invariants. Rather than extending debate or relying on hierarchical arbitration, the SSS applies constrained motion (spin) within an invariant-anchored field to allow inputs to self-sort by stability. Outcomes resolve deterministically into assimilation, rejection, or diagnostic flagging, without discretionary judgment. The method is scale-independent, memoryless yet history-consistent, and self-auditing via emergent geometric patterns. The SSS is positioned as a post-debate convergence mechanism for research prioritisation, systems design, policy filtering, and SDOP enforcement, where cost-of-delay exceeds cost-of-decision. Keywords decision convergence; post-debate collapse; invariant-first design; motion-based sorting; spiral dynamics; self-auditing systems; SDOP; diagnostic geometry; constraint-driven reasoning