Model Management under Finite Conditions: A Diagnostic and Decision Architecture for Validity, Friction, and Revision

Finite cognitive systems organize experience, stabilize reference, and guide expectations and action without fully surveying their presuppositions and consequences. Stabilized orders support orientation but can be overextended or continued inappropriately. This paper develops a programmatic diagnostic and decision architecture for managing such orders, particularly their elaborated forms as models. Examining the claim architecture connects units of reference, claims, domains, scope, test conditions, and couplings. Validity is understood as domain-bound viability under strain; friction denotes an epistemically readable mismatch of an activated stabilized order under its operating conditions. The architecture separates assessments of validity from decisions about continued use. Rules for opening, redistribution, and abandonment structure exploration, attribution of findings, and the justification of correction, revision, suspension, replacement, or abandonment. The social conditions for testing in distributed epistemic and model management are also considered. A boundary case of personal identity examined through epistemic critique and an internal, LLM-assisted comparison involving the Allegheny Family Screening Tool challenge different parts of the program. The comparison with a strong disciplinary baseline establishes no general superiority. LLM judges rated certain additional contributions concerning claim specification, model identity, transfer of findings, and justification of revision as substantive. Their soundness by disciplinary standards, generalizability, and practical utility have not been independently confirmed. The architecture is not a decision algorithm and replaces neither disciplinary procedures nor normative justification. Its supplementary aim is to make the testing, use, and revision of stabilized orders and models more controllable and correctable across everyday, scientific, technical, and institutional contexts of cognition.