1. Data in pragmatic research

Andreas H. Jucker, Klaus P. Schneider, W. Bublitz
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引用次数: 5

Abstract

This introductory chapter gives a broad-brush overview of the various types of data in the field of empirical research in pragmatics. It starts with a discussion of the various types of analytical units in pragmatics, taking as its starting point single utterances, which are contrasted to smaller units, such as deictic elements, stance markers, discourse markers, hedges and the like, as well as to larger units, such as sequences of utterances and entire discourses. Data for pragmatic research comes in different modalities. Spoken language and written language are the most obvious modalities, but digital language with its own complexities, sign language and non-verbal behaviour have recently become increasingly important as data for pragmatic research. Moreover, research data can be categorised on the basis of their location on four scalar dimensions. The first dimension concerns the amount of constraints on the interactants and the allowable contributions. The second dimension scales the level of fictionality or factuality of the language under observation. The third dimension assesses the amount of research interference in the production of the data, and the fourth dimension, finally, situates data according to the researcher focus between the two poles of small amounts of highly contextualized data to big data searches of largely decontextualized phenomena.
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1. 语用研究中的数据
这一引言章对语用学实证研究领域的各种类型的数据进行了粗略的概述。本文首先讨论了语用学中各种类型的分析单位,以单个话语为出发点,将其与指示要素、立场标记、话语标记、模糊限制语等较小的单位以及话语序列和整个话语等较大的单位进行对比。实用主义研究的数据有不同的形式。口语和书面语是最明显的形式,但数字语言具有其自身的复杂性,手语和非语言行为最近成为语用研究的重要数据。此外,研究数据可以根据其在四个标量维度上的位置进行分类。第一个维度涉及交互器的约束数量和允许的贡献。第二个维度衡量被观察语言的虚构或真实程度。第三个维度评估研究对数据产生的干扰程度,最后,第四个维度根据研究人员的关注点将数据置于少量高度情境化的数据和大量非情境化现象的大数据搜索之间的两极之间。
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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8. Introduction to part 3: Experimentational pragmatics 14. Ethnographic methods in pragmatics 20. Corpus annotation 16. Discourse analysis Frontmatter
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