A Structural Review Framework for Mid- to Long-Term Governance in Digital Responsibility Management

This project presents a structural review framework for examining mid- to long-term governance continuity in the context of digital responsibility management. Rather than evaluating performance outcomes or causal effects, the study focuses on the structural relationship between original governance planning documents and subsequent implementation records over extended time horizons. The proposed framework adopts a document-based qualitative review approach, systematically comparing planning assumptions, strategic orientations, and responsibility allocations with later execution trajectories. Observed discrepancies are classified as structural alignment, strategic adjustment, or structural drift, with the aim of restoring accountability visibility and interpretive clarity in governance processes that unfold across multiple years and institutional layers. Generative AI is incorporated strictly as a constrained support tool for document organization and semantic alignment. It does not participate in judgment, categorization, or interpretation, thereby preserving human responsibility attribution and avoiding epistemic displacement. The framework is designed to be repeatable and adaptable, serving as a governance review mechanism rather than an audit or performance evaluation instrument. This work is methodological and conceptual in nature. It is intended as an openly accessible research object that contributes to discussions on accountable governance, digital responsibility management, and long-term institutional planning, particularly in digitally mediated environments where governance assumptions and execution realities may diverge over time.