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Human beings encounter recurrent situations in which feeling, attention, motivation, interpretation, and action become organized around consequential relationships and responsibilities. These experiences also acquire public expression through roles, narratives, images, and rituals. This article develops an archetypal organization framework to explain how psychological coordination and cultural meaning can become connected. An archetypal organization is a recurrent pattern of coordination around a consequential life problem, specified by relational and task structure, regulatory priorities, and maintenance and transition rules. An archetypal functional state is an individual's situated realization of that pattern. The framework proposes that recurring demands and feedback stabilize coordination among psychological processes, while cultural expression makes aspects of these patterns communicable and available for subsequent interpretation and action. It distinguishes structural correspondence, symbolic feedback, and historical formation as separate explanatory questions. Caregiving, companionship, intimate partnership, leadership, and heroic engagement illustrate the framework; a worked caregiving example shows how changing need, responsibility, and identity meaning can yield different transition paths despite similar initial behavior. Five empirical propositions address configuration transfer, relational redirection, transition sensitivity, cultural correspondence, and structure-sensitive symbolic feedback. A staged research program combines behavioral tasks, cultural analysis, and intensive longitudinal methods. The framework's contribution lies in organizing established mechanisms into a common explanatory structure while making stronger claims about particular configurations and cross-level relations independently assessable. Theoretical preprint; no new empirical dataset. Correspondence: fengli@eudavia.org AI assistance: OpenAI-based AI assistants and Gemini 4 Argon were used for literature discovery, critical discussion, drafting, revision, and language review. AI-generated suggestions were assessed against the manuscript and relevant sources. This assistance was substantive, not limited to grammar correction. AI systems are not authors, and AI-based review is not independent peer review. The named human author is responsible for the published work.
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Feng Li (2026) studied this question.
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