KJCKorea
Journal Central

This paper presents the results of a section of a larger study which aimed to examine the way magistrates and judges (collectively termed Judicial Officers) work with interpreters in Australian courts. The study included observations of court proceedings with interpreters around Australia (New South Wales, Tasmania, Queensland, Victoria, Northern Territory and Western Australia) and interviews with Judicial Officers and interpreters, with questions specifically related to the implementation of the Recommended National Standards for Working with Interpreters in Courts and Tribunals (RNS). The current paper presents the results of the interviews with 19 interpreters from 17 languages. The interviews explored the interpreters’ experiences and perspectives regarding the ways in which Judicial Officers communicate with and through them in bilingual proceedings, and their perceptions about the level of implementation of the RNS since its inception in 2017.

Seunghyuk Choi (2025). An Analysis of Conjunctive Expressions in Chinese–Korean Translation by Generative AI. This study analyzes how the Korean connective endings ‘-고’ and ‘-며’ are translated when generative AI translates Chinese asyndetic compound sentences into Korean, with the aim of identifying tendencies and limitations in AI handling of conjunctive relations. By comparing the translated texts of ChatGPT and HyperCLOVA X using newspaper articles and public speeches, the study reveals that generative AI often relies on surface-level paratactic structures without fully inferring the underlying logical relationships required by context. Consequently, the use of ‘-고’ and ‘-며’ tends to be excessively concentrated on the enumerative function, leading to weakened logical cohesion in the translated texts. Based on these findings, the study suggests enhancing AI translation quality through improved semantic inference of conjunctive relations and incorporating cohesion-based evaluation metrics that assess the accuracy of logical linkage in generative AI translation. (Chung-Ang University, Korea)

Jooeun Kim (2025). Gender Inequality Expressions in Korean Media and Their Russian Translations: A Focus on Fan Translations. This study investigates how gender-discriminatory expressions in Korean media content are rendered in Korean–Russian fan translations and evaluates the extent to which the translated expressions convey the original intent and emotional tone. The dataset consists of dramas and films released between 2013 and 2024, and the types of discriminatory expressions were systematically classified based on Cho Tae-rin (2006). The findings reveal that terms such as ajumma are often neutralized or distorted in translation, resulting in the loss of the original discriminatory nuances. Furthermore, the unofficial nature of fan translations leads to inconsistent translation quality, while cultural differences frequently hinder the accurate transmission of meaning. To address these challenges, this study emphasizes the need to enhance translators’ cultural competence and linguistic proficiency through education and to establish a systematic translation review process. Overall, this research contributes to translation studies, cultural studies, and linguistics by identifying key issues in translating discriminatory expressions and proposing strategies for the global dissemination of Korean content. (Hankuk University of Foreign Studies, Korea)