Of professionals, non-professionals and everything in between: redefining the notion of the ‘translator’ in the crowdsourcing era

IF 0.7 3区 文学 Q3 COMMUNICATION
Miguel A. Jiménez-Crespo
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The study concludes that published materials in themselves do not display the potential to impact the status of translators negatively, but rather the opposite: the website materials reinforce that for some content types or high-quality levels, high levels of expertise and professionalism are required. Nevertheless, this might not be necessary for all translation projects, content types and-or client needs.KEYWORDS: Crowdsourcingpaid crowdsourcingcorpus studiestranslators’ statustranslation quality Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1. See Jiménez-Crespo (Citation2017a, 73–82) for further information about approaches to text segmentation in crowdsourcing workflows.2. Meaning that single texts are not routinely divided into chunks and distributed to a collective of freelance translators using a crowdsourcing workflow.3. For example, Textmaster includes the following formulations that associate translation competence levels to price tiers (1) ‘Native translators approved by Textmaster/non full time’ (2) ‘Native translators approved by Textmaster – full time’ or (3) ‘Specialist native professional translators’. These levels are also associated to different types of content. This is the full description for the ‘Standard level’: ‘Standard level is provided by native translators who have been tested and approved by Textmaster, translating in addition to their other professional activities. It is suitable for simple translations of short texts without specific vocabulary’ (Textmaster Citation2023).4. Sketchengine is an online corpus analysis tool that allows to automatise a number of corpus processing and corpus analysis tasks (https://www.sketchengine.eu/, last accessed 13 September 2023).5. Additional corpus data has been added to the GitHub repository: https://github.com/jiménezmiguel/The_Translator_Paid_Crowdsourcing (last accessed 15 September 2023).6. For a description of the differences between wordlists and wordsketch visualisations in Sketchengine, see Kocincová et al (Citation2015).7. The complete data for the Wordsketch for the lemma ‘translator’, including frequency and scores, can be found in the GitHub repository: https://github.com/jiménezmiguel/The_Translator_Paid_Crowdsourcing (last accessed 15 September 2023).8. The complete data for the Wordsketch for the lemma ‘quality’, including frequency and scores, can be found in the GitHub repository at https://github.com/jiménezmiguel/The_Translator_Paid_Crowdsourcing (last accessed 15 September 2023).9. 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引用次数: 1

Abstract

ABSTRACTThis paper studies the potential impact of ‘paid translation crowdsourcing’ on translators’ status through a corpus study of discourses found in language industry websites. It has been argued in Translation Studies literature that in this model crowdsourcing companies attempt to redefine translation ‘professionalism’ or ‘competence’ as a monolithic notion to include a dynamic range of price segments supposedly associated with degrees of translation competence and fitness-for-purpose. The results of the corpus study show that industry websites present a range of ‘expertise’ or ‘skillset’ in which different levels of translation competence associated with different content types and fit-for-purpose tiers coexist. The study concludes that published materials in themselves do not display the potential to impact the status of translators negatively, but rather the opposite: the website materials reinforce that for some content types or high-quality levels, high levels of expertise and professionalism are required. Nevertheless, this might not be necessary for all translation projects, content types and-or client needs.KEYWORDS: Crowdsourcingpaid crowdsourcingcorpus studiestranslators’ statustranslation quality Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1. See Jiménez-Crespo (Citation2017a, 73–82) for further information about approaches to text segmentation in crowdsourcing workflows.2. Meaning that single texts are not routinely divided into chunks and distributed to a collective of freelance translators using a crowdsourcing workflow.3. For example, Textmaster includes the following formulations that associate translation competence levels to price tiers (1) ‘Native translators approved by Textmaster/non full time’ (2) ‘Native translators approved by Textmaster – full time’ or (3) ‘Specialist native professional translators’. These levels are also associated to different types of content. This is the full description for the ‘Standard level’: ‘Standard level is provided by native translators who have been tested and approved by Textmaster, translating in addition to their other professional activities. It is suitable for simple translations of short texts without specific vocabulary’ (Textmaster Citation2023).4. Sketchengine is an online corpus analysis tool that allows to automatise a number of corpus processing and corpus analysis tasks (https://www.sketchengine.eu/, last accessed 13 September 2023).5. Additional corpus data has been added to the GitHub repository: https://github.com/jiménezmiguel/The_Translator_Paid_Crowdsourcing (last accessed 15 September 2023).6. For a description of the differences between wordlists and wordsketch visualisations in Sketchengine, see Kocincová et al (Citation2015).7. The complete data for the Wordsketch for the lemma ‘translator’, including frequency and scores, can be found in the GitHub repository: https://github.com/jiménezmiguel/The_Translator_Paid_Crowdsourcing (last accessed 15 September 2023).8. The complete data for the Wordsketch for the lemma ‘quality’, including frequency and scores, can be found in the GitHub repository at https://github.com/jiménezmiguel/The_Translator_Paid_Crowdsourcing (last accessed 15 September 2023).9. Blacklists are commonly used in keywords analyses in corpus studies to eliminate high frequency function words such as pronouns, determinants, common prepositions, etc.10. https://www.sketchengine.eu/ententen-english-corpus/ (last accessed 13 September 2023).Additional informationFundingThis work was supported by the Rutgers Council Grant; Research Council, Rutgers, The State University of New Jersey.Notes on contributorsMiguel A. Jiménez-CrespoMiguel A. Jiménez-Crespo is a Professor in the Department of Spanish and Portuguese at Rutgers University, where he directs the MA program in Spanish Translation and Interpreting. He holds a PhD in Translation and Interpreting Studies from the University of Granada, Spain. His research focuses on the intersection of translation theory, translation technology, digital technologies and artificial intelligence, corpus-based translation studies and translation training. He is the author of Localization (Routledge, forthcoming), Crowdsourcing and Online Collaborative Translations: Expanding the Limits of Translation Studies (John Benjamins, 2017) and Translation and Web Localization (Routledge, 2013). His papers have appeared in the top -tier Translation Studies journals such as Target: international journal of translation studies, Meta: journal des traducteurs, Perspectives: Studies in Translatology, Linguistica Antverpiensia, TIS: Translation and Interpreting Studies, Jostrans: The journal of specialized translation, Translation and Interpreting, or Translation, Cognition and Behavior. He has been a member of the board of the American Translation and Interpreting Studies Association (ATISA) since 2012.
专业人士,非专业人士以及介于两者之间的一切:在众包时代重新定义“翻译”的概念
摘要本文通过对语言产业网站话语的语料库研究,探讨了“付费翻译众包”对译者地位的潜在影响。翻译研究文献认为,在这个模型中,众包公司试图将翻译“专业性”或“能力”重新定义为一个整体概念,包括与翻译能力和目的适用性程度相关的动态价格区间。语料库研究的结果表明,行业网站呈现出一系列“专业知识”或“技能集”,其中与不同内容类型和适合目的层次相关的不同水平的翻译能力共存。研究得出的结论是,出版材料本身并没有显示出对翻译人员地位产生负面影响的潜力,相反,网站材料强调,对于某些内容类型或高质量水平,需要高水平的专业知识和专业精神。然而,这可能不是所有翻译项目、内容类型和/或客户需求都需要的。关键词:众包付费众包语料库研究译者地位翻译质量披露声明作者未发现潜在利益冲突。关于众包工作流程中文本分割方法的更多信息,请参阅jimsamnez - crespo (Citation2017a, 73-82)。这意味着单个文本不会被常规地分成大块,并通过众包工作流程分发给一群自由译者。例如,Textmaster包含以下公式,将翻译能力水平与价格等级相关联(1)“经Textmaster批准的本地翻译/非全职”(2)“经Textmaster批准的本地翻译-全职”或(3)“专业的本地专业翻译”。这些级别还与不同类型的内容相关联。这是“标准级别”的完整描述:“标准级别是由经过Textmaster测试和认可的本地翻译提供的,除了翻译他们的其他专业活动之外。它适用于没有特定词汇的短文本的简单翻译”(Textmaster Citation2023)。4 . Sketchengine是一个在线语料库分析工具,它允许自动执行许多语料库处理和语料库分析任务(https://www.sketchengine.eu/,最后访问日期为2023年9月13日)。额外的语料库数据已被添加到GitHub存储库中:https://github.com/jim samnezmiguel /The_Translator_Paid_Crowdsourcing(最后访问日期为2023年9月15日)。关于Sketchengine中单词列表和wordsketch可视化之间差异的描述,请参见kocincov等人(Citation2015)。7 .词理“翻译器”的Wordsketch的完整数据,包括频率和分数,可以在GitHub存储库中找到:https://github.com/jim nezmiguel/The_Translator_Paid_Crowdsourcing(最后访问日期为2023年9月15日)。Wordsketch的引理“质量”的完整数据,包括频率和分数,可以在GitHub存储库中找到https://github.com/jim nezmiguel/The_Translator_Paid_Crowdsourcing(最后访问日期为2023年9月15日)。黑名单是语料库研究中常用的关键词分析方法,用于剔除高频功能词,如代词、行列式、常用介词等。https://www.sketchengine.eu/ententen-english-corpus/(最后访问日期为2023年9月13日)。本研究由罗格斯大学理事会资助;研究委员会,罗格斯大学,新泽西州立大学。作者简介:作者是罗格斯大学西班牙语和葡萄牙语系教授,指导西班牙语翻译和口译硕士项目。他拥有西班牙格拉纳达大学翻译研究博士学位。他的研究主要集中在翻译理论、翻译技术、数字技术和人工智能、基于语料库的翻译研究和翻译培训的交叉领域。他著有《本地化》(Routledge出版社,即将出版)、《众包和在线协作翻译:拓展翻译研究的局限》(John Benjamins出版社,2017)和《翻译和网络本地化》(Routledge出版社,2013)。曾在《Target:国际翻译研究期刊》、《Meta:译者期刊》、《Perspectives: Studies in transllatology》、《Linguistica Antverpiensia》、《TIS: Translation and Interpreting Studies》、《Jostrans: the journal of specialized Translation》、《翻译与口译》、《翻译、认知与行为》等翻译研究顶级期刊发表论文。自2012年以来,他一直是美国翻译和口译研究协会(ATISA)的董事会成员。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Translator
Translator Multiple-
CiteScore
1.20
自引率
14.30%
发文量
22
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