A theory-driven candidate annotation architecture for collective regulation under stress in human-centered computational psychiatry: early modern Iberia as a worked coding demonstration

Computational psychiatry has advanced formal accounts of individual prediction, affect regulation, and maladaptive rigidity, but it still has fewer clinically interpretable tools for representing social and institutional processes under collective stress. This Hypothesis and Theory article proposes a theory-driven candidate annotation architecture for this purpose. It defines five collective-process variables—defensive closure (DEF-C), collective anxiety load (ANX-C), integrative progression (PRO-C), punitive superegoic regulation (SUP-C), and moral frame rigidity (FRAME-C)—as theory-guided interpretive indicators for trained human annotation and later formal modeling. Drawing on Active Inference, PAD-S/CSA, Conceptual Metaphor Theory, Moral Politics, social defense theory, and threat-rigidity research, the framework specifies how historically or institutionally situated material can be parsed through explicit coding units, evidence spans, ordinal ratings, confidence markers, adjudication rules, variable-overlap handling, and prospective disconfirmation criteria. Early modern Iberia serves as a worked coding demonstration, with an internal contrast between layered plurality under c