(untitled) (Contemporary Education and Teaching Research, 2026)
At a historical juncture when Artificial Intelligence Generated Content (AIGC) is profoundly reshaping global knowledge production and the landscape of geopolitical analysis, traditional area studies confront a dual crisis: the declining explanatory power of qualitative paradigms and a “knowledge supply crisis” mediated by algorithmic systems. This paper argues that area studies must undergo a paradigmatic transformation—from “linguistic mediation” to “semantic governance,” and from tacit experiential knowledge to the construction of “semantic infrastructure.” By conceptualizing high-quality data annotation as both a confirmation of semantic rights and the building of cognitive infrastructure, the study proposes an integrated framework encompassing ontology construction, semantic alignment, and domain-specific evaluation. Through this engineering-oriented architecture, unstructured regional knowledge can be transformed into structured data assets. Driven by a dual-engine model integrating “United Nations normative corpora” and “Open Source INTelligence (OSINT),” area studies can evolve from post hoc interpretation toward a decision-support paradigm characterized by real-time perception, structured computation, and scenario simulation. Such a transformation will consolidate the epistemic foundations of China’s autonomous knowledge system and safeguard national cognitive sovereignty.