Complexity science has produced powerful descriptive tools, yet it still lacks a shared structural language for intervention—a gap that lies not in method but in the problem domain. This paper argues that the proper question for the study of complex systems is not "what a system is" but "how a system sustains itself amid flux," and that governance is where this question becomes operational. AI governance, climate governance, financial stability, and urban emergency response repeatedly encounter the same kind of predicament—multi-agent self-adaptation, cross-level temporal asynchrony, and constraint structures that lose their adjustability under pressure—yet there is no common structural language for comparing and transferring lessons among them. This paper argues that the root of this predicament lies not in specific methods but in a triple misalignment among problem domain, epistemology, and methodology: these fields confront a problem domain of "how a system sustains itself amid flux," while employing an epistemology of "what a system is" and a methodology of "describing the system." Problem domain, epistemology, and methodology are three facets of a single structure; misaligned, they fail together; aligned, they succeed together. The paper offers an operationalization of this alignment—a general structural grammar—comprising five basic constituents, a logical walkthrough from diagnosis to action (using platform governance as a simplified scenario), differential criteria against existing frameworks, and a four-rung validation ladder. It should be noted up front: this paper provides a logical demonstration; empirical validation is deferred to future work (see Section 8).
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Ning Kaifeng (2026) studied this question.
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