Japanese scientists’ English for research publication purposes

Leigh McDowell
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Abstract

Error Analysis was developed by early Second Language Acquisition (SLA) researchers as a way to investigate interlanguage and better understand the second-language learning processes. While it is no longer an active branch of research in SLA, it remains a useful tool for those concerned with accuracy in language use. Given the elevated importance of accuracy in English for Research and Publication Purposes (ERPP), this may be one area where Error Analysis may continue to inform research and praxis. The high degree of language precision demanded in ERPP contexts can be a source of frustration for many engaged in scholarly publication, especially those for whom English is an additional language, such as the Japanese scientists studied in this paper. For Japanese scientists and possibly others, an empirical profile of their most frequent error patterns may help them to better deal with accuracy in research writing. With this motivation, this study applies a corpus-assisted error analysis framework to quantify sentence-level grammar errors and identify the most frequent error patterns in the research article manuscripts of Japanese scientists. A corpus of 53 research article manuscripts with 4,495 errors comprises the primary data. Additionally, two raters and a comparison of errors from scientists from six different L1 backgrounds are employed to triangulate the data and investigate the reliability and generalizability of the findings. Findings reveal that the top ten most frequent errors comprise 52.9%, or half of all errors in the corpus, and are dominated by errors with determiners and prepositions.
日本科学家的研究出版英语
错误分析是早期第二语言习得(SLA)研究人员开发的一种研究语际和更好地理解第二语言学习过程的方法。虽然它已不再是 SLA 研究的一个活跃分支,但对于那些关注语言使用准确性的人来说,它仍然是一个有用的工具。鉴于准确性在研究和出版英语(ERPP)中的重要性,这可能是错误分析法继续为研究和实践提供信息的一个领域。对于许多从事学术出版的人来说,ERPP 中对语言准确性的高要求可能会让他们感到沮丧,尤其是那些英语是外语的人,比如本文中研究的日本科学家。对于日本科学家和其他可能的科学家来说,对他们最常见的错误模式进行实证分析可能有助于他们更好地处理研究写作中的准确性问题。基于这一动机,本研究采用语料库辅助错误分析框架来量化句子级语法错误,并识别日本科学家研究文章手稿中最常见的错误模式。主要数据由 53 篇研究文章稿件组成的语料库提供,其中包含 4,495 个错误。此外,为了对数据进行三角测量,研究结果的可靠性和可推广性,还采用了两名评分员,并对来自六种不同语言背景的科学家的错误进行了比较。研究结果表明,最常见的前十个错误占语料库中所有错误的 52.9%,即一半,主要是定语和介词错误。
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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CiteScore
2.20
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