基于语料库的中华人民共和国立法文书模糊语言研究

发布时间：2018-06-19 04:18

本文选题：模糊 + 中国立法　；参考：《浙江大学》2017年硕士论文

【摘要】：在语言学研究和话语分析中,模糊现象研究都非常重要。不像有些语言学概念那样简单易懂,模糊现象非常抽象而晦涩,其定义及分类也非常困难。模糊现象存在极为普遍,广泛存在于并且被有意或者无意地应用于诸多语言类型当中,并且承担不同的功能。鉴于模糊现象如此之重要,对其进行深入而详细的研究则显得非常有意义。立法语言作为一种语言变体,与其它语言变体大不相同,举例来说,其与文学语言、计算机语言、新闻媒体语言等都不尽相同。因为立法语言有其独特的语言特征,比如准确性和简洁性等。立法语言深受不同的政治制度和法律体系的影响,中华人民共和国的政治制度和法律体系与世界上其它国家的有很大的不同;因此,中国的立法语言的特征必定与其它国家的立法语言的特征相异。立法语言中的语言模糊现象非常耐人寻味,其可以被定义为立法语言中的某些语言成分的语义是开放的,这些语言成分的语义边界模糊不清。本文将模糊语言分为模糊形容词、模糊副词、模糊名词和模糊动词四类,并从不同视角去解释这一现象。本论文基于语料库来研究中国立法文书中的语言模糊现象,聚焦于大语料库中模糊语言的统计学分析和定量分析,该大语料库由多达96部中国立法文书构成,其中有大约1,200,400汉字。论文布局由数据支撑和说明,使得论文论述较为客观而具有较强的说服力。根据中华人民共和国法律体系的划分,中国特色社会主义法律体系大致由七大分支组成。因此,整个大语料库又相应地分为七个子语料库。随后使用Wmatrix和Antconc这两个知名度高和接受度高的语言分析工具对每个子语料库进行加工。Wmatrix有许多功能,比如语义标记、词类标记,而且可以制出词频列表,同时应用语料库语言学理论来建立、加工和分析语料库。当七个子语料库被Wmatrix的USAS标记工具标记之后,模糊成分将会被特定的标记词标记出来,这使得模糊成分的分类成为可能。然后根据标记词将所有的模糊成分划分为模糊形容词、模糊副词、模糊名词和模糊动词,随后这些模糊成分被从语料库中抽取出来,计算个数及其占总词数的百分比,之后用SPSS和对数似然比计算器对数据进行处理获得显著性差异值。同时,基于法学理论和七个子语料库的实证数据,对中国立法语言中的模糊现象的功能和影响带来的启示进行分析。本研究最终取得六大发现,每个子语料库中,在模糊形容词、模糊副词、模糊名词和模糊动词当中,模糊名词使用百分比最高;大部分模糊成分都属于概括性和抽象的词汇;在七个子语料库中,宪法及其相关法语料库中的模糊形容词、模糊副词、模糊名词和模糊动词使用百分比最高;在每个子语料库中,模糊副词的使用百分比最低;每个子语料库内部模糊成分使用频率没有明显显著性差异;七个子语料库之间模糊成分使用频率有显著性差异。同时表明模糊现象在中国立法中具有概括功能、行为引导功能和维持法律解释弹性空间的功能。
[Abstract]:In linguistic and discourse analysis, the study of fuzzy phenomena is very important. Unlike some linguistic concepts that are so easy to understand, fuzzy phenomena are very abstract and obscure, and their definitions and classifications are also very difficult. The legislative language, as a variant of the language, is very different from other language variants. For example, it is different from literary language, computer language, new media language, etc. because the legislative language has a different language. Its unique linguistic features, such as accuracy and simplicity. The legislative language is deeply influenced by different political and legal systems, and the political and legal systems of People's Republic of China are very different from those of other countries in the world. Therefore, the characteristics of the legislative language of China must be characterized by the characteristics of the legislative language of other countries. The linguistic vagueness in the legislative language is very intriguing. It can be defined as the opening of some linguistic elements in the legislative language. The semantic boundaries of these languages are blurred. This paper divides fuzzy languages into four categories: fuzzy adjectives, fuzzy adverbs, vagueness nouns and fuzzy verbs, and from different perspectives This paper is based on a corpus to study the linguistic fuzziness in Chinese legislative documents, focusing on the statistical analysis and quantitative analysis of the vague language in a large corpus. The large corpus is composed of up to 96 Chinese legislative documents, including about 1200400 Chinese characters. It is more objective and persuasive. According to the division of the legal system of People's Republic of China, the legal system of socialism with Chinese characteristics is roughly composed of seven branches. Therefore, the whole large corpus is divided into seven sub corpus accordingly. Then, the two well-known and highly accepted languages are used by Wmatrix and Antconc. .Wmatrix has many functions for processing each sub corpus, such as semantic markers, word class markers, and word frequency lists, and corpus linguistics theory to build, process and analyze corpus. When seven sub corpus are marked by Wmatrix's USAS markup tool, the fuzzy components will be marked by specific markers. Words are marked out, which makes the classification of fuzzy components possible. Then, according to the markers, all the fuzzy components are divided into fuzzy adjectives, fuzzy adverbs, fuzzy nouns and fuzzy verbs, and then these fuzzy components are extracted from the corpus, calculated the number and the percentage of the total number of words, and then use SPSS and log likelihood ratio. The calculator deals with the significant difference in data processing. At the same time, based on the empirical data of the legal theory and the seven sub corpus, this paper analyzes the functions and implications of the ambiguity in the Chinese legislative language. This study finally obtains six major discoveries, in each sublanguage, the fuzzy adjectives, the fuzzy adverbs, and the fuzzy names. Among the words and fuzzy verbs, the percentage of fuzzy nouns is the highest; most of the fuzzy components belong to the general and abstract words; in the seven sub corpus, the fuzzy adjectives, the fuzzy adverbs, the fuzzy nouns and the fuzzy verbs are the highest in the Constitution and its related French database; in each sub corpus, the fuzzy adverb is made. With the lowest percentage, there is no significant difference in the frequency of the use of fuzzy components in each sub corpus; there are significant differences in the frequency of the use of fuzzy components between the seven sub corpus.
【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：H136

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