Purpose
This study examines how the use of generative artificial intelligence (AI) in research may be interpreted and regulated under South Korea’s National Research and Development Innovation Act and its Enforcement Decree. It also evaluates how AI-assisted research practices challenge the conceptual boundaries of the statutory categories of research misconduct. Methods: Through doctrinal legal analysis of Article 31 of the Act and Article 56 of the Enforcement Decree, common AI-assisted practices across the research cycle—design, literature review, data generation and analysis, manuscript writing, and the input of data into AI systems—were mapped to the Act’s misconduct taxonomy and related legal duties. Results: Generative AI may plausibly implicate fabrication, falsification, plagiarism, and improper authorship (Article 31(1)1), as well as improper ownership of research and development outcomes and breaches of security measures (Article 31(1)3–4). The analysis further indicates that AI use destabilizes categorical boundaries, as individual outputs may simultaneously involve invented content, distorted interpretation, and unattributed reproduction. Numerous research-integrity risks arise from failures in research processes, including nondisclosure, inadequate verification, weak provenance tracking, and irreproducible analysis pipelines. Conclusion: Legal and institutional responses should prioritize transparency across the research cycle and the development of auditable workflows, rather than focusing solely on sanctioning problematic outputs. Clear disclosure standards, verification obligations, reproducibility requirements, and stringent data-stewardship rules are necessary to address these emerging risks.

PURPOSE
This study conducted to identify the effect of learning organization construction and learning orientation on organizational effectiveness among hospital nurses. Method: Data was collected from convenient sample of 296 nurses who worked for the major hospitals in Seoul, Gyeonggi-do and Gangwoen-do. The self-reported questionnaire was used to assess the general characteristics, the level of the learning organization construction, learning orientation and organizational effectiveness. The data were analyzed using descriptive statistics, pearson's correlation coefficient and multiple regression. Result: The mean score of learning organization construction was 3.61(+/-.32), learning orientation got 3.26(+/-.39), and organizational effectiveness obtained 3.38(+/-.42). The learning organization construction affects of organizational effectiveness by 44.18% and learning orientation by 37.43%.
CONCLUSION
This finding indicates that learning organization construction and learning orientation affects the nurses' organizational effectiveness in hospital.

Citations

• Effects of Emotional Competence, Learning Organization, and Nursing Organization Culture among Nursing Performance of Clinical Nurses
  Yu-Mi Yun, Myung-Sook Yoo
  The Korean Journal of Health Service Management.2017; 11(4): 29.     CrossRef
• A Review of Research on Evaluation Indexes and Determinants of Organizational Effectiveness of Hospital Nursing Organizations
  Jieun Kim, Jinhyun Kim
  Perspectives in Nursing Science.2014; 11(1): 49.     CrossRef
• The Effects of Learning Orientation on Self-Efficacy and Innovation Behaviors
  Sang-Kyu Hwang
  Journal of the Korea Safety Management and Science.2014; 16(2): 175.     CrossRef