A Multifactorial Analysis of Concessive Clause Positioning

IF 0.7 2区 文学 0 LANGUAGE & LINGUISTICS
Huimyung Kang, Jiajin Xu
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引用次数: 1

Abstract

ABSTRACT Previous works have identified multiple factors and their interplay that condition the positioning of the concessive adverbial clauses. This study continues this line of research by 1) focusing exclusively on the positioning of although-led concessive adverbial clauses (although-clauses hereafter) among different concessive clause relations; 2) supplementing the factor set with more linguistic features, such as sentence-initial adverbials and hedging terms; and, 3) extending and generalizing the scope of competition among semantic, discoursal and processing motivators to a higher-level competition between ‘clarity’ and ‘processability’. Data were retrieved from 1,738 concessive sentences of student argumentative essays from the BAWE and NESSIE corpora. Models were generated based on binary logistic regression and random forests. The results show that the motivator of the relationship between the although-clauses and their main clauses was the most significant variable in all models, denoting its priority in conditioning concessive clause positioning, under the Competition Model framework. Subordinate clause complexity and deranking (i.e. clauses that do not have a full verb) were the least significant among all motivating factors. Overall, clarity-related motivators outweigh processability-related ones, prioritizing clear meaning-conveying in competition with processing motivators.
让步条款定位的多因素分析
以往的工作已经确定了制约让步状语从句定位的多种因素及其相互作用。本研究继续了这一研究路线:1)专门关注尽管引出的让步状语从句(尽管从句在下文中)在不同让步从句关系中的定位;2) 为因子集补充更多的语言特征,如句首状语和对冲词;以及,3)将语义、话语和加工动机之间的竞争范围扩展和概括为“清晰度”和“可加工性”之间的更高层次竞争。从BAWE和NESSIE语料库中检索了1738篇学生议论文的让步句。模型是基于二元逻辑回归和随机森林生成的。结果表明,在竞争模型框架下,尽管从句及其主从句之间关系的激励因素是所有模型中最显著的变量,表明其在条件让步从句定位方面具有优先地位。在所有的激励因素中,从句的复杂性和去链接(即没有完整动词的从句)是最不重要的。总的来说,与清晰度相关的动机超过了与可加工性相关的动机,在与加工动机的竞争中,优先考虑清晰的意思传达。
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
CiteScore
2.90
自引率
7.10%
发文量
7
期刊介绍: The Journal of Quantitative Linguistics is an international forum for the publication and discussion of research on the quantitative characteristics of language and text in an exact mathematical form. This approach, which is of growing interest, opens up important and exciting theoretical perspectives, as well as solutions for a wide range of practical problems such as machine learning or statistical parsing, by introducing into linguistics the methods and models of advanced scientific disciplines such as the natural sciences, economics, and psychology.
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