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Title: Evaluation of popular science translation : a case study on the Universe in a Nutshell
Authors: Huang, Qingling
Keywords: Humanities::Language
Issue Date: 2019
Abstract: The present research aims to develop a translation quality assessment (TQA) model that is suitable for popular science translation and is easy to apply, using a translation of Stephen Hawking’s the Universe in a Nutshell as a case study. The study begins by examining the purposes and characteristics of scientific translation to offer a particular perspective on the features and text functions of the source text concerned. In what follows, the study reviews the literature on existing qualitative and quantitative TQA models, taking into consideration their relevance to popular science translation in an effort to formulate and propose a framework incorporating assessment at both micro- and macro-textual levels through four primary dimensions. The four dimensions are Accuracy, Fluency, Information flow, Style/Textuality, with the first two covering micro-textual assessment and the last two covering macro-textual assessment, respectively. Each primary dimension can be further expanded into finer evaluation components. Mindful of the apprehension and reservation critics have on substandard translations in popular science genre, the analysis in the present case study draws heavily on unsatisfactory or erroneous translations in formulating the assessment tool and hopefully that will help raise awareness about potential pitfalls. The framework also incorporates error severity, qualitatively categorizing errors as critical, major or minor depending on their impact to the target readers. The core of the present study applies the proposed TQA model to evaluate GuǒKé Zhōng De YŭZhòu《果壳中的宇宙》, which is the Universe in a Nutshell translated to simplified Chinese by Wu Zhongchao. Unlike sparse and fragmentary comments about errors in this particular rendition, this present research produces a comprehensive and systematic evaluation for a convincing conclusion on the overall quality of translation. It identifies 810 errors in the translated text under review, categorizes them according to the evaluation components, and visualises the findings in terms of severity of mistreatment and distribution across chapters highlighting ‘hard-hit’ aspects that would rip and tear apart a translation. The study goes further to suggest alternative translations or improvement in alignment with the evaluation criteria to demonstrate the successful application of the proposed model as well as its suitability and feasibility for popular science translation.
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
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