Analysis of Translation Shifts Using Systemic Functional Linguistics: Textuality of news translation between Japanese and English

Translated news are target-oriented and therefore translation shifts are general practice in news translation. However, little research has been conducted to reveal specific shifts involving English and Japanese. With a view to contribute to translator training, the main objective of this project is to establish patterns and motivations of shifts in news translation between English and Japanese. Two types of shifts are investigated. First, information content; additions, deletions or moves, and second, information flow, focusing on Theme. This project is corpus-based and a specialised corpus is compiled, consisting four sub-corpora; original news articles in English and in Japanese, their translations into Japanese and into English. They form parallel corpora as well as comparable. All the data are manually annotated for additions, deletions and moves and also for Theme using the UAM CorpusTool, adopting Systemic Functional Linguistics as framework for analysis. Literature claims most news articles undergo additions, deletions or moves during translation. In my study, additions are more common in English translations while in Japanese translations it is deletions. Rank-wise, below-the-clause shifts occur throughout the text while above-the-clause shifts tend to occur towards the beginning or end of the text. Regarding information flow, general trend of Theme realisation in translated news are similar to that of the TL in general. In addition Theme choice at the beginning of text units moves towards the TL norm, while still showing the ST influence. Particular types of Theme appear exclusively at specific locations in text in Japanese translation, in line with the non-translation Japanese texts. This suggests genre conventions of the TL are at work in Theme choice. News translation into English and Japanese indicates processes of standardisation and ST interference. Shifts concerning information content and flow are motivated by the genre conventions and the target reader’s relevance to and expectations for news articles.