This chapter develops an integrated design architecture for generative relational research. Building on the preceding chapters on research praxis, relational inquiry, and generative methodology, it shifts the unit of analysis from individual methods to the organization of an entire research project. The chapter connects research questions, theory, case and field selection, data, representation, methodological portfolios, method sequencing, cross-method adjudication, model–evidence dialogue, sensitivity, robustness, uncertainty, historical re-epistemization, AI-assisted research, governance, documentation, reproducibility, reusability, cumulative research, theory development, research decision making, model functions across praxis modes, and provisional closure. Throughout, research design is treated as a revisable relational architecture in which evidence, concepts, models, interpretations, institutional conditions, normative inputs, and practical consequences remain mutually connected. Particular attention is given to preserving disagreement, uncertainty, provenance, alternative models, superseded interpretations, category histories, and reopening conditions. The chapter also clarifies the transition from research-dominant to application-dominant praxis by distinguishing epistemic closure from practical authorization and by examining how the function of evidence and models changes when inquiry begins to support consequential action. The resulting framework presents integrated research design as a recursive, historically situated, and governable process capable of supporting cumulative inquiry while preserving epistemic openness and future reinterpretability.
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Wanhong HUANG (2026) studied this question.
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