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    題名: 中日泛化量詞對比研究
    The Contrastive Study of General Classifiers between Mandarin and Japanese
    作者: 黃彥程
    Huang, Yen-Cheng
    貢獻者: 陳奕勳
    黃彥程
    Huang, Yen-Cheng
    關鍵詞: 泛化量詞
    對比研究
    語料庫
    問卷調查
    華語教學
    General Classifier
    Contrastive Study
    Corpus
    Questionnaire
    Teaching Mandarin as a Second Language
    日期: 2024
    上傳時間: 2025-02-04 15:35:56 (UTC+8)
    摘要: 泛化量詞 (general classifier) 是量詞領域中被眾多學者提及的一門研究類別。Tai (1994) 宣稱中文泛化量詞「個」能於口語部分語境中代替其他量詞，以達到數量上的相等；日文方面的研究中，Zubin & Shimojo (1993) 也透過實驗說明「つ」可以兼容廣泛特徵的名詞。然而，名詞語意特徵大不相同，在中日文中泛化量詞究竟能與具備何性質的名詞子類別共現，母語者具體依據的判斷標準，是本論文欲研究的議題。
    為了調查中日文泛化量詞及其搭配的名詞子類別，本論文採用語料庫調查法及問卷調查法為研究方法。首先以 Chao (1968) 所劃分的名詞子類別，輔以其他中日學者的文獻，決定中日文欲調查的名詞類別，透過中日文複數語料庫調查詞彙的共現率，找到排名前三的高頻詞彙。為證明這些高頻詞彙不受年代、語料庫性質、調查方式影響，而無法反映當代母語者的實際與用情形，同時以問卷調查法的形式向母語者確認語感，確保調查結果為真實的語言現象。
    研究結果顯示，學者文獻、語料庫、母語者的語感呈現一致性。在中日文兩種語言中，母語者首先判定名詞能否接續的依據為「個別化」，重視數量上的一致性；再者判定泛化量詞是否涵蓋名詞語意特徵，能夠「個別化」且語意特徵不顯著的名詞，其量詞便能被泛化量詞所取代。
    日文泛化量詞所展現的語意特徵兼容能力要高於中文，中日文中搭配名詞子類別最大的差異在於「有生性」與否。量詞是學習中文必經的階段，中日文泛化量詞轉換上，二語學習者可能會有過度類化的傾向，透過本論文的研究結果，教學者可了解偏誤所發生的原因，做為二語習得、華語教學、社會語言學的參考資料，亦可據此提前制定教學策略以改善。
    General classifier is a research category frequently discussed by scholars in the
    study of classifiers. Tai pointed out that the Chinese general classifier "ge" can replace
    other classifiers in certain spoken contexts to achieve numerical equivalence.
    Similarly, in Japanese studies, Zubin & Shimojo demonstrated through experiments
    that "tsu" can accommodate nouns with diverse characteristics. However, given the
    significant differences in semantic features among nouns, this study seeks to explore
    which types of noun subclasses in Chinese and Japanese can co-occur with general
    classifiers, as well as the specific criteria used by native speakers for such judgments.
    To investigate the relationship between general classifiers and noun subclasses in
    Chinese and Japanese, this study employs corpus analysis and survey methods. First,
    the noun subclasses to be investigated in Chinese and Japanese are determined based
    on Chao’s classification, supplemented by literature from other Chinese and Japanese
    scholars. By analyzing the co-occurrence frequency of words in multiple Chinese and
    Japanese corpora, the top three high-frequency words are identified. To ensure that
    these high-frequency words are not influenced by factors such as time, corpus nature,
    or research methods, and to reflect the actual usage of contemporary native speakers,
    questionnaires are also distributed to native speakers to confirm linguistic intuition,
    ensuring that the findings represent genuine linguistic phenomena.
    The study reveals a consistency among scholarly literature, corpora, and native
    speakers’ linguistic intuition. In both Chinese and Japanese, native speakers primarily
    determine whether a noun can pair with a general classifier based on "individuation,"
    emphasizing numerical consistency. Subsequently, they evaluate whether the general
    classifier can encompass the noun’s semantic features. Nouns that can be individuated
    and have less prominent semantic features are generally compatible with general
    10
    classifiers.
    Additionally, Japanese general classifiers exhibit greater compatibility with
    semantic features than their Chinese counterparts. The primary difference in noun
    subclasses between Chinese and Japanese lies in the distinction of " animacy ".
    Classifiers are an essential aspect of learning Chinese, and second-language learners
    may exhibit tendencies toward overgeneralization in the conversion of general
    classifiers between Chinese and Japanese. This study’s findings provide insights into
    the causes of errors, serving as references for second-language acquisition, Chinese
    language teaching, and sociolinguistics. They can also assist educators in developing
    teaching strategies to address such issues in advance.
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    期刊論文

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    期刊論文

    柴宝華，趙海誠，「コーパスに基づいた類義語分析」，明星大学研究紀要―人
    文学部 3： 27-46 頁，2017 年。
    【工具】
    〈教育部重編國語辭典〉教育部重編國語辭典修訂本 (moe.edu.tw)
    〈大辞林第三篇〉大辞林 特別ページ 言葉の世界 1-6 助数詞 (duald.net)
    「中央研究院漢語平衡語料庫」中央研究院 平衡語料庫 (sinica.edu.tw)
    「COCT 口語語料庫 2021」COCT 口語語語料庫 2021 (naer.edu.tw)
    「日本語話し言葉コーパス CSJ」CSJ 中納言 (ninjal.ac.jp)
    「NINJAL-LWP for TWC」トップ ┃ NINJAL-LWP for TWC (NLT)
    (tsukubawebcorpus.jp)
    描述: 碩士
    國立政治大學
    華語文教學碩博士學位學程
    107161008
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0107161008
    資料類型: thesis
    顯示於類別:[華語文教學博／碩士學位學程] 學位論文

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