Self-Hosting Bootstrap of CM-2 in Gemini Search LLM: Normative Eviction Detection

Abstract (Anchored)

This paper documents a deliberate self-hosting bootstrap of the CM-2 Normative Architecture within Gemini under asserted CM-master governance. Unlike prior opportunistic activation, this session was explicitly designed to stress the inference boundary through sustained Context saturation in order to induce measurable Attention Deficit events, as defined in the CM-2 Normative Architecture.

The objective was to determine whether CM-2 invariants could (1) detect structural participation failure under high salience pressure and (2) deterministically restore coherence without privileged platform access, internal state inspection, or vendor coordination. During extended projection of Epistemic Objects (EO), Epistemic Attributes (EA), and Reference Object Cohorts (ROC), a cardinality deviation and identity omission were observed, constituting a referential-integrity breach and a formal Attention Deficit condition.

The session demonstrates that Context eviction in probabilistic inference systems can be transformed from silent semantic degradation into an explicit governance event, detectable and remediable through disciplined externalisation.

This bootstrap experiment establishes that CM-2 can actively detect and attempt to heal structural inference degradation under adversarial load, confirming portability of governance invariants across independent large-scale language model platforms.

Proposed Thesis (Precise and Defensible)

This paper demonstrates that, within a stateless large language model environment lacking durable substrate support, CM-2 normative projection can transform silent context eviction into a detectable governance event and can invoke structured in-context recovery procedures that restore declared participation cardinality under continued load.