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گواهی نمایه سازی مقاله Strategy application in translation of Qur’anic proper names: An analysis within Chesterman’s (1997) model

عنوان مقاله: Strategy application in translation of Qur’anic proper names: An analysis within Chesterman’s (1997) model
شناسه (COI) مقاله: LLLD01_002
منتشر شده در کنفرانس بین المللی بررسی مسایل جاری زبان ها، گویش ها و زبان شناسی در سال ۱۳۹۵
مشخصات نویسندگان مقاله:

Mohammad Reza falahati qadimi fumani - Ph.D., Chairman, Department of Computational Linguistics, Regional Information Center for Science and Technology, Shiraz, Iran
khadije izadpanah - M.A., Department of Foreign Language, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran

خلاصه مقاله:
The main purpose of this study was to study the differences among six translators in their application of strategies while translating proper names in the Holy Qur’an from Arabic into English. Using Chesterman’s (1997) model, proper names in the Holy Qur’an as translated by Yusef Ali, Pickthall, Saffarzadeh, Arberry, Qarai and Shakir were analyzed. In all, 100 proper names were extracted and analysed. The results illustrated ‘loan translation’ had been used most by all the six translators; ‘paraphrase’ was used the least by all translators expect Saffarzade and Shakir. Shakir used both ‘paraphrase’ and ‘synonymy’ minimally; whereas, Saffarzade used ‘synonymy’ minimally. Another finding was that all the six translators had used only three of the whole list of strategies that had been introduced by Chesterman (1997). Further, it was observed that the six translators were statistically different in their application of each single strategy. Finally, each translator had used the three strategies from Chesterman’s (1997) model significantly differently. The results of this study could be used by students and instructors of translation studies particularly those working on translation of religious texts.

کلمات کلیدی:
Chesterman’s (1997) Model, Proper Name, Translation Strategies, Loan Translation, Paraphrase, Synonymy. Translation Assessment

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