
This paper proposes an evolutionary-functional framework for understanding metacognitive control mechanisms. Departing from normative accounts of cognition as an "ideal observer" or "truth-seeker," we posit that cognitive architectures are optimized for risk minimization and uncertainty management rather than veridical representation. We introduce "Architectural Irreducibility" as a fundamental safeguard against the formation of chronically maladaptive global models. Metacognition is framed not as an auxiliary high-level faculty, but as a structural necessity emerging from hierarchical complexity and the partial autonomy of regulatory loops. The framework delineates specific architectural layers — from reflexive processing to metacognitive monitoring — and their functional roles in preventing what we term "false global confidence."
Predictive Processing, Computational Psychiatry, Active Inference, Cognitive Architecture, Metacognition, Precision Weighting
Predictive Processing, Computational Psychiatry, Active Inference, Cognitive Architecture, Metacognition, Precision Weighting
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