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Developing Linguistic Literacy: Perspectives from Corpus Linguistics and Multi-Dimensional Analysis

机译：发展语言文化：语料库语言学与多维分析的视角

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In their conceptual framework for linguistic literacy development, Ravid u26 Tolchinsky synthesize research studies from several perspectives. One of these is corpus-based research, which has been used for several large-scale research studies of spoken and written registers over the past 20 years. In this approach, a large, principled collection of natural texts (a u27corpusu27) is analysed using computational and interactive techniques, to identify the salient linguistic characteristics of each register or text variety. Three characteristics of corpus-based analysis are particularly important (see Biber, Conrad u26 Reppen 1998):(1) a special concern for the representativeness of the text sample being analysed, and for the generalizability of fndings; (2) overt recognition of the interactions among linguistic features: the ways in which features co-occur and alternate; (3) a focus on register as the most important parameter of linguistic variation: strong patterns of use in one register often represent only weak patterns in other registers. Corpus studies have documented the linguistic differences among spoken and written registers in English and other languages. Further, by analyzing systematic corpora produced by students at different stages, these same techniques have been used to track the patterns of extended language development associated with literacy. Two major patterns emerge from studies in this research tradition: (1) adult written language is dramatically different from natural conversation; and (2) written language is by no means homogeneous: rather, there are major linguistic differences among written registers. Thus, the developmental acquisition of linguistic literacy requires control over the patterns of register variation, in addition to a mastery of the mechanics of the written mode.
机译：Ravid Tolchinsky在其语言素养发展的概念框架中，从多个角度综合了研究。其中之一是基于语料库的研究，在过去的20年中，该研究已用于口头和书面语体的几项大规模研究。在这种方法中，使用计算和交互技术来分析大量的，有原则的自然文本（a u27corpus u27），以识别每个寄存器或文本变体的显着语言特征。基于语料库的分析的三个特征特别重要（请参见Biber，Conrad，1998年，Reppen，1998年）：（1）特别关注要分析的文本样本的代表性以及查找的概括性； （2）公开认识语言特征之间的相互作用：特征同时出现和交替的方式； （3）关注寄存器是语言变异的最重要参数：在一个寄存器中使用强模式通常仅表示在其他寄存器中的弱模式。语料库研究已经记录了英语和其他语言的口语和书面语之间的语言差异。此外，通过分析学生在不同阶段产生的系统语料库，这些相同的技术已被用来追踪与识字相关的扩展语言发展模式。在这种研究传统中，研究产生了两种主要模式：（1）成人书面语言与自然对话大不相同； （2）书面语言绝不是同质的：相反，书面语种之间存在主要的语言差异。因此，对语言素养的发展习得，除了要掌握书面模式的技巧外，还需要控制寄存器变化的模式。

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