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作 者:刘振前[1] 阿卜杜外力.热合曼 徐万治[2] LIU Zhenqian;XU Wanzhi China(Abuduwaili REHEMAN Shandong Universit;University of Petroleu)
机构地区:[1]山东大学 [2]中国石油大学(华东)
出 处:《现代外语》2018年第5期633-646,共14页Modern Foreign Languages
基 金:山东大学优秀博士研究生创新能力提升计划资助
摘 要:学界对一般会话含义的理解主要有两种对立模式:默认模式和未指定模式。前者认为,一般会话含义基于语言特征而非语境信息自动获得;后者则认为,一般会话含义的理解需要依靠语境,且需付出一定的认知努力。本研究使用鼠标跟踪范式,考察了一般会话含义在中性、上限和下限语境中的在线理解过程。结果表明,一般会话含义比所言或可替代意义优先获得,其加工速度快、过程较易,但不同含义类型对语境的依赖程度不同。因此,两种经典模式均不能充分解释该结果。本文认为,一般会话含义的理解之所以优先,是因为与其相关的诸多条件得到了满足,因此满足制约条件的模式更具解释力。There are two competitive models concerning the interpretation of generalized conversational implicatures. The Default Model contends that generalized conversational implicatures are linked to the linguistic properties of utterances and are generated automatically and largely independent of context. By contrast, the Underspecified Model has it that generalized conversational implicatures are contextually dependent with their processing requiring much cognitive effort. To test the two models, two experiments were conducted employing the mouse- tracking paradigm. Online processing of generalized conversational implicatures was examined in neutral, upper-bounded and lower-bounded contexts respectively. The results demonstrate that generalized conversational implicatures were accessed more accurately, quickly and smoothly than the literal or other meanings of the target utterances. However, different types of implicatures differed in their degree of dependence on contexts. While presenting evidence against the two classical models, these results lend support to the rapid integration of multiple cues associated with generalized implicatures, as predicted by the Constraint-based Model.
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