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研究生: 張建斌
Chien-Pin Chang
論文名稱: 中文形容詞呈現之性別概念
Gender Representations Manifested in Chinese Adjectival Compounds
指導教授: 蘇席瑤
Su, Hsi-Yao
學位類別: 碩士
Master
系所名稱: 英語學系
Department of English
論文出版年: 2008
畢業學年度: 96
語文別: 英文
論文頁數: 157
中文關鍵詞: 社會語言學中文性別年齡篇章分析詞彙語義學語料庫問卷刻板印象社會變遷複合詞搭配詞語言歧視Google
英文關鍵詞: Sociolinguistics, Mandarin Chinese, gender, age, Discourse Analysis, Lexical Semantics, corpus, questionnaire, stereotype, social change, compound, collocation, language bias, Google
論文種類: 學術論文
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  • 在中文裡,當帶有某種性別特徵之詞素與其他字結合為複合詞,此複合詞通常帶有此性別特徵。但事實上,部份複合詞並非如此呈現。此論文旨在探討此種中文複合形容詞中所呈現之不對稱現象與其所代表之意涵。此研究選擇「狂」、「豪」、「柔」、「溫」、「正」五個詞素所構成之二十三個複合形容詞作為研究對象。研究結合了語料庫與問卷兩種方法,同時採用此兩種方法使得研究更為全面性。
    此研究選擇網路作為語料庫來源,Google則為語料蒐集之工具。複合形容詞與男性或者女性共現之語料(共蒐集690筆)為語料庫研究分析對象。此外,共有108名男性與127名女性參與問卷研究。根據年齡,受試者之後也被區分為兩組。受試者在問卷的三個部份中,分別被要求判斷每個複合形容詞之性別連結偏向、表達對於複合形容詞之感受程度、提供這些複合形容詞之代表人物。
    語料庫研究之結果發現,複合形容詞之性別偏向可能受到多種原因影響,例如形容詞本身之語義偏向、網路及媒體之影響、社會風氣之改變。另外,傾向女性之複合形容詞時常帶有負面意涵。相同的複合形容詞與男性或女性連結,亦可能產生不同的意涵。這些結果某種程度上反映出一般人所抱持之刻版印象。
    在問卷方面,結果顯示刻板印象仍深入影響人們對複合形容詞之看法。對於複合形容詞與性別之連結,女性與年輕人看法較顯彈性。另外受試者大多偏好男性傾向之複合形容詞與排斥女性傾向之複合形容詞。然而,女性雖排斥女性傾向形容詞,但對此類形容詞接受度仍較高。此現象亦反映了女性在語言中的弱勢地位。問卷中不同年齡層之受試者選擇偏好亦有其差異,而此差異也反映了某種程度之社會變遷。在代表人物部份,女性受試者較常為某些被偏好的男性傾向複合形容詞提供女性作為代表人物;兩年齡層相互比較亦可發現男女意象之改變。比較兩種研究方法結果顯示網路與大眾媒體可能是造成兩種研究結果差異之主因。
    期望藉由中文複合形容詞與男女之共現研究,我們能更深入的探知詞義反映社會價值之現象。

    In Mandarin Chinese, when a morpheme biased towards a given gender combines with another word to form a compound, this compound tends to maintain the gender connotation of the biased morpheme. However, some compounds do not reveal this tendency. This thesis aims to investigate such unequal phenomena found in some Chinese gendered adjectival compounds and their linguistic effects and connotations. We focus on the following five characters and their adjectival compounds (23 in total): kuang (狂), hao (豪), rou (柔), wen (溫), and zheng (正). This thesis combines two approaches, including a corpus-based approach and questionnaire collection. The two approaches complement each other.
    The search engine “Google” was chosen as the tool to access our corpus—the web. Tokens in which a compound was used to modify people were included for analysis, and there were 690 tokens collected in total. In addition, we recruited 108 men and 127 women, and the participants were further divided into two age groups. The participants were asked to judge a compound’s likelihood to collocate with men and women, express their feeling about a compound when it is used to describe them, and provide a representative figure for each compound.
    The results of the corpus-based study show that each adjectival compound has its collocational preference, which may result from diverse factors, including the original semantic features of the compounds, the influence of the Internet and mass media, social trends, etc. In addition, it is observed that female-inclined compounds carry negative meanings more often. When a compound co-occurs with different genders, different meanings and connotations might be generated. The results to some degree reflect the stereotypes people generally hold.
    The questionnaire reveals the great influence of gender stereotypes on people’s perceptions of the compounds. The female participants’ and the junior group’s answers are also found to be more flexible in that the boundaries between masculine and feminine compounds are not as absolute as before. Additionally, it is found that male-inclined words are usually preferred, while most female-inclined words are dispreferred. However, women are adapted to these words more often. Women’s disadvantageous language position is observed. The different preferences of the junior group and the senior group also suggest the change of social trends. Furthermore, it is also discovered that the female participants are more likely to provide female representative figures for a preferred male-inclined compound. Through the comparison between the junior group’s and the senior group’s answers, it is also found that the images of men and women are changing. Finally, the discrepancies between the two approaches display the influence of the Internet and mass media.
    It is hoped that by observing some gendered adjectival compounds in Mandarin Chinese, we can gain a deeper understanding of how lexical meanings can reflect social values.

    Chinese Abstract i English Abstract iii Acknowledgements v Table of Contents vii List of Tables xi List of Figures xii Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Background 2 1.3 Research Questions 3 1.4 Significance of the Thesis 5 1.5 Organization of the Thesis 6 Chapter 2 Literature Review 7 2.1 Gender Studies 7 2.1.1 Wollstonecraft (1792) 7 2.1.2 Mill (1869) 9 2.1.3 Woolf (1929, 1938) 9 2.1.4 De Beauvoir (1949) 10 2.1.5 Money et al. (1968), Money and Ehrhardt (1972) 11 2.1.6 Other Related Studies 12 2.2 Gendered Language and Gender Biases in the Western Society 13 2.2.1 Lakoff (1975, 1990) 13 2.2.2 Schulz (1975) 14 2.2.3 Tannen (1993, 1994) 15 2.2.4 Sutton (1995) 16 2.2.5 Fowler (1991) 17 2.2.6 Caldas-Coulthard (1995) 18 2.2.7 Other Related Studies 19 2.3 Gendered Language and Gender Biases in Chinese 20 2.3.1 Shih (1984) 20 2.3.2 Shieh (1997) 22 2.3.3 Liao (2000) 23 2.3.4 Lin (2004) 23 2.4 Gender Stereotype 25 2.4.1 Basow (1992) 25 2.4.2 Zou (1986) 25 2.4.3 Visser (2002) 26 2.4.4 Litoselliti (2006), Caldas-Coulthard (1996) 27 2.5 Social Change 28 2.5.1 Luo (1981) 28 2.5.2 Lin (1998) 28 2.5.3 Other Related Studies 29 2.6 Collocation 30 2.6.1 Firth (1957) 30 2.6.2 Benson et al. (1986, 1997) 31 2.6.3 Sinclair (1991) 32 2.6.4 Stubbs (2001a, 2001b, 2002) 32 2.7 Chapter Summary 33 Chapter 3 Methodology 35 3.1 The Corpus-Based Approach (Discourse Analysis) 35 3.1.1 Adjectival Compounds 35 3.1.2 Tool 37 3.1.3 Sampling Method 40 3.2 Questionnaires 41 3.2.1 Participants 41 3.2.2 Questionnaire Design 43 3.2.3 Procedure 44 3.2.4 Analysis Procedure 45 3.3 Chapter Summary 46 Chapter 4 Results and Analyses 48 4.1 The Corpus-Based Approach (Discourse Analysis) 48 4.1.1 Kuang (狂) 49 4.1.1.1 Kuangwang (狂妄) 49 4.1.1.2 Kuangye (狂野) 51 4.1.1.3 Kuangfang (狂放) 52 4.1.1.4 Fengkuang (瘋狂) 52 4.1.1.5 The association with men and women 53 4.1.2 Hao (豪) 54 4.1.2.1 Haoqi (豪氣) 54 4.1.2.2 Haomai (豪邁) 55 4.1.2.3 Haoshuang (豪爽) 55 4.1.2.4 Haofang (豪放) 56 4.1.2.5 The association with men and women 57 4.1.3 Rou (柔) 58 4.1.3.1 Jiaorou (嬌柔) 58 4.1.3.2 Roumei (柔媚) 58 4.1.3.3 Rouruo (柔弱) 59 4.1.3.4 Roushun (柔順) 59 4.1.3.5 Wenrou (溫柔) 60 4.1.3.6 Yinrou (陰柔) 61 4.1.3.7 The association with men and women 62 4.1.4 Wen (溫) 63 4.1.4.1 Wenliang (溫良) 63 4.1.4.2 Wenhe (溫和) 64 4.1.4.3 Wenhou (溫厚) 65 4.1.4.4 Wenwen (溫文) 66 4.1.4.5 Wenshun (溫順) 67 4.1.4.6 The association with men and women 67 4.1.5 Zheng (正) 68 4.1.5.1 Zhengdian (正點) 68 4.1.5.2 Zhengzhi (正直) 69 4.1.5.3 Gangzheng (剛正) 69 4.1.5.4 Zhengjing (正經) 70 4.1.5.5 The association with men and women 71 4.2 Questionnaires 71 4.2.1 Part One 71 4.2.1.1 The overall tendency of the 23 adjectival compounds 72 4.2.1.2 The discrepancies between male and female participants 73 4.2.1.3 The discrepancies between the junior group and the senior group 74 4.2.1.4 The interaction between gender and age factors 76 4.2.2 Part Two 77 4.2.2.1 The overall tendency of the participants’ preference 78 4.2.2.2 The discrepancies between male and female participants 78 4.2.2.3 The discrepancies between the junior group and the senior group 80 4.2.2.4 The interaction between gender and age factors 82 4.2.3 Part Three 84 4.2.3.1 The overall tendency of the 23 adjectival compounds 84 4.2.3.2 The discrepancies between male and female participants 86 4.2.3.3 The discrepancies between the junior group and the senior group 88 4.3 The Discrepancy between Two Approaches 89 4.4 Chapter Summary 92 Chapter 5 General Discussion 94 5.1 The Corpus-Based Approach (Discourse Analysis) 94 5.2 Questionnaires 97 5.2.1 Part One 97 5.2.2 Part Two 99 5.2.3 Part Three 100 5.3 The Comparison between Two Approaches 102 5.4 Chapter Summary 104 Chapter 6 Concluding Remarks 106 6.1 Summary of the Major Findings 106 6.2 Implications of the Study 109 6.3 Suggestions for Future Research 110 References 111 Appendix A Questionnaire 117 Appendix B Corpus Data 122

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