KJCKorea
Journal Central

Medical practice is a multi-layered phenomenon characterized by systemic complexity, epistemicuncertainty, and outcome‑oriented nature. However, legal discourse in medical litigation oftenreduces this complexity by employing active/passive grammatical constructions, framing clinician–patient interactions in terms of a simplistic offender/victim binary. In response, this article introducesthe concept of the middle-voice, defined by two grammatical features: (1) the internal involvementof human and non-human elements in the occurrence of action, and (2) the dynamic emergenceof action through contextual interactions. It proposes a middle-voice structure that incorporatesantecedent-condition clauses, inanimate subject constructions, and the Korean “-ge doeda” form(equivalent to the English verb “become”). This framework supports the development of middlevoicejustice, which moves beyond adversarial models and promotes a more inclusive culture ofmedical accountability and safety. By offering a theoretical basis for institutional applications, such asin the design of apology laws, this approach enables more accurate descriptions of medical accidents,more balanced attributions of responsibility, and reconsideration of the institutional foundationsnecessary for a just medical culture.

The evidence advisory system (EAS) is often criticized for serving to legitimize governmentpreferredpolicies rather than facilitating independent deliberation. Underlying this critique is a morefundamental question: Is expertise compatible with democratic governance? This article addressesthat question by advancing two arguments in support of democratic expertise. First, drawingon theories of deliberative democracy, it argues that the epistemic authority of experts dependslargely on the active judgment of citizens. The formation of expert consensus, which is central toEAS operations, is discussed as a working example. Second, using the framework of the politics ofevidence, it contends that the legitimacy of the EAS hinges on institutional arrangements that enablethe effective and democratic use of evidence. Together, these arguments clarify how ordinary citizenscan develop the deliberative capacities needed to engage critically with expert knowledge.

This article explores how the traditional framework of research ethics must be redefined in responseto the ethical challenges posed by the academic use of generative artificial intelligence (Gen AI). As Gen AI technologies become increasingly integrated across various stages of research—fromstudy design and data analysis to manuscript writing—they offer notable gains in efficiency, whilesimultaneously expanding ethical gray areas. In particular, issues such as factual inaccuracies andhallucinations, violations of privacy and copyright, ambiguous authorship, and the deskilling ofresearchers are becoming increasingly entangled, posing serious threats to the credibility andintegrity of academic work. To address these concerns, the article proposes four core ethicalprinciples suited to the Gen AI era: truthfulness and explainability, respect for intellectual property,field-specific guidelines, and the cultivation of researcher competence. The central concern is notmerely whether such technologies should be adopted, but rather how the identity and responsibilityof researchers, and the sustainability of scholarly communities, can be ethically restructured in theface of transformative technological change.