科学语言的中间和跨学科研究:研究人员面临的实质和方法挑战

Kalbotyra Pub Date : 2015-05-21 DOI:10.15388/Klbt.2013.7671
Jolanta Šinkūnienė
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引用次数: 1

摘要

学术语篇分析的最新趋势表明,学术界对学术语篇的跨学科和跨语言变化有着浓厚的兴趣。虽然大多数研究仍然是关于英语的,但最近几十年,人们对其他语言的学术话语产生了浓厚的兴趣,经常将其与英美科学文本的写作和论证模式进行比较。许多研究试图勾勒出学术话语的普遍特征,并突出一些特定的特征,这些特征仅在某些学科或文化社区中具有代表性。因此,学术话语的特征往往是在“大”(即国家)和“小”(即学科)文化背景下解释的(参见Atkinson 2004)。本文简要回顾了当前学术话语研究的趋势,主要是研究文章的类型。本文的目的是讨论学术话语研究人员在为他们的跨学科和跨语言分析编写专门的可比语料库时面临的挑战,并强调在这种分析中重要的某些方法问题。正如该领域的许多研究人员所指出的那样,结果的可靠性和更好的经验基础主要取决于适当选择的比较共同基础。最近发表的关于学术话语的跨语言和跨学科方面的研究综述揭示了语料库设计和数据分析的各种方法解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tarpkalbiniai ir tarpdalykiniai mokslo kalbos tyrimai: medžiagos ir metodų pasirinkimo iššūkiai tyrėjams
Recent trends in academic discourse analysis reveal a keen scholarly interest in cross-disciplinary and cross-linguistic variation in academic texts. While most of the research is still on the English language, the last few decades have seen an upsurge of interest in academic discourse produced in other languages, frequently comparing it to patterns of writing and argumentation in Anglo-American scientific texts. Numerous studies attempt to outline the universal features of academic discourse as well as to highlight the specific ones, typical only of some of the disciplines or cultural communities. Thus, features of academic discourse are often interpreted within the “big” (i. e. national) and “small” (i. e. disciplinary) culture context (cf. Atkinson 2004). The paper briefly reviews trends in current academic discourse research, mainly in the genre of the research article. The purpose of the paper is to discuss the challenges that researchers of academic discourse face while compiling specialized comparable corpora for their cross-disciplinary and cross-linguistic analyses and to highlight certain methodological issues which are important in this type of analyses. As noted by many researchers in the field, the reliability of the results and a better empirical grounding primarily depend on the appropriately selected common ground of comparison. An overview of recently published research on cross-linguistic and cross-disciplinary aspects of academic discourse reveals various methodological solutions to corpus design and data analysis.
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