Explicitation in the Translation of Sci-tech Texts: A Case Study of Articles on IEA and the Chinese Government Official Websites

In the context of scientific and technological globalization, accurate and efficient translation of sci-tech texts is of paramount importance. Employing a qualitative case study methodology, this research investigates the application of explicitation strategies in translation using seven energy-related documents (2019-2022) from the International Energy Agency (IEA) and the Chinese government websites. These documents are selected for their high relevance to contemporary energy policy discourse and manifestation of typical genre features. Drawing upon principles from contrastive analysis and explicitation theory, the research examines translation practices at lexical, syntactic, and discourse levels to elucidate how translators render implicit information explicit, thereby enhancing translational clarity and accuracy. Analysis reveals that specific strategies are employed: at the lexical level, annotation and contextual adaptation clarify specialized terminology; at the syntactic level, structural transformation and clause adaptation bridge structural divergences between English and Chinese; and at the discourse level, logic explicitation and adjustments in cohesion (omission/addition) address coherence gaps. The research finds that the appropriate application of these explicitation strategies significantly improves translation quality by ensuring terminological precision, resolving structural ambiguities, and clarifying logical connections for target readers. These improvements contribute to reducing the cognitive load for target readers by aligning translations with their linguistic expectations, thereby promoting more effective international sci-tech exchange and cooperation. Acknowledging the limitations inherent in the small sample size of this study, we recommend expanding the corpus to other sci-tech fields for future research. Such expansion would provide more targeted and extensive theoretical and practical guidance for the translation of diverse scientific texts, ultimately promoting global sci-tech knowledge exchange and collaborative development.

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Publication Details

Journal
International Journal of Chinese and English Translation & Interpreting
Published
2025-06-18
DOI
https://doi.org/10.56395/htwr4f31
Primary Topic
Natural Language Processing Techniques
Type
article
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article

Explicitation in the Translation of Sci-tech Texts: A Case Study of Articles on IEA and the Chinese Government Official Websites

Xu Zhou
International Journal of Chinese and English Translation & Interpreting
Natural Language Processing Techniques
article

Explicitation in the Translation of Sci-tech Texts: A Case Study of Articles on IEA and the Chinese Government Official Websites

Xu Zhou
article en

Abstract

In the context of scientific and technological globalization, accurate and efficient translation of sci-tech texts is of paramount importance. Employing a qualitative case study methodology, this research investigates the application of explicitation strategies in translation using seven energy-related documents (2019-2022) from the International Energy Agency (IEA) and the Chinese government websites. These documents are selected for their high relevance to contemporary energy policy discourse and manifestation of typical genre features. Drawing upon principles from contrastive analysis and explicitation theory, the research examines translation practices at lexical, syntactic, and discourse levels to elucidate how translators render implicit information explicit, thereby enhancing translational clarity and accuracy. Analysis reveals that specific strategies are employed: at the lexical level, annotation and contextual adaptation clarify specialized terminology; at the syntactic level, structural transformation and clause adaptation bridge structural divergences between English and Chinese; and at the discourse level, logic explicitation and adjustments in cohesion (omission/addition) address coherence gaps. The research finds that the appropriate application of these explicitation strategies significantly improves translation quality by ensuring terminological precision, resolving structural ambiguities, and clarifying logical connections for target readers. These improvements contribute to reducing the cognitive load for target readers by aligning translations with their linguistic expectations, thereby promoting more effective international sci-tech exchange and cooperation. Acknowledging the limitations inherent in the small sample size of this study, we recommend expanding the corpus to other sci-tech fields for future research. Such expansion would provide more targeted and extensive theoretical and practical guidance for the translation of diverse scientific texts, ultimately promoting global sci-tech knowledge exchange and collaborative development.

International Journal of Chinese and English Translation & Interpreting
China University of Mining and Technology (CN)
Openalex Percentile: Top 93%
Natural Language Processing Techniques
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