The Coherence Emergence Identity Model (CEIM): Identity Debt, Collapse-Phase Traversal, and Neurodivergent Variation Formalising Crisis Dynamics, Therapeutic Leverage, and the Alexian Recursion Operator within the CEIM Framework

<p>Papers 1 and 2 of the CEIM series laid out the structural and dynamic foundations of identity: the Sensory–Meaning–Behaviour (SMB) cycle forms the cognitive core, where meaning comes before awareness, and the Coherence Emergence Identity Model (CEIM) maps how successive Self-States (SSs) merge into a stable Global Self-State (GSS) attractor shaped by Meanture. Paper 3 builds on this by exploring identity stress, debt build-up, and collapse-phase traversal within Alexian Dynamics, a formal model describing identity evolution under sustained pressure and phase transitions. This framework uses the Alexian Recursion Operator (ℛ) and Alexian State Space concepts to explain coherence breakdown, phase boundary crossing, and strategies for reorganizing after collapse.&nbsp;&nbsp;</p> <p><span>Identity debt (????) is the accumulated cost of long-term misalignment between enacted and endorsed self-states—a slow-growing coherence load that distorts the attractor landscape and narrows the crisis horizon. Collapse-phase traversal is the abrupt shift across identity manifolds when coherence drops below the Meanture-dependent threshold; it’s not failure, but a phase change following the same principles as physical transitions. The Alexian Recursion Operator formalizes the full identity update cycle—from SS creation through GSS integration, debt adjustment, and post-traversal reorganization into attractors—as a single, mathematically closed operation on the identity manifold.&nbsp;&nbsp;</span></p> <p><span>This paper derives the crisis horizon as a function of debt growth rate, shame–debt coupling, and discharge coefficient, yielding a closed-form point at which coherence collapse is inevitable. It also defines neurodivergent profiles as systematic parameter shifts in Alexian Dynamics, reflecting characteristic differences in Mean…&nbsp;&nbsp;</span></p>