Effects of semantic and pragmatic factors on preschool children's negation-triggered inferences on possible alternatives

被引:0
|
作者
Zhang, Xiaowen [1 ]
Zhou, Peng [2 ]
机构
[1] Tsinghua Univ, Beijing 100084, Peoples R China
[2] Zhejiang Univ, Hangzhou 310058, Peoples R China
基金
中国国家自然科学基金;
关键词
Cognitive development; Language acquisition; Negation; Inference; Pragmatics; Early semantic network; COMPREHENSION; KNOWLEDGE; FLEXIBILITY; CONTEXT;
D O I
10.1016/j.jecp.2024.106057
中图分类号
B844 [发展心理学(人类心理学)];
学科分类号
040202 ;
摘要
Negation-triggered inferences are universal across human languages. Hearing "This is not X" should logically lead to the inference that all elements other than X constitute possible alternatives. However, not all logically possible alternatives are equally accessible in the real world. To qualify as a plausible alternative, it must share with the negated element as many similarities as possible, and the most plausible one is often from the same taxonomic category as the negated element. The current article reports on two experiments that investigated the development of preschool children's ability to infer plausible alternatives triggered by negation. Experiment 1 showed that in a context where children were required to determine the most plausible alternative to the negated element, the 3-, 4- and 5-year-olds, exhibited a robust preference for the taxonomic associates. Experiment 2 further demonstrated that the 3-, 4- and 5-year-olds considered all the complement set members as equally possible alternatives in a context where they were not explicitly required to evaluate the plausibility of different candidates. Taken together, our findings reveal interesting developmental continuity in preschool children's ability to make inferences about plausible alternatives triggered by negation. We discuss the potential semantic and pragmatic factors that contribute to children's emerging awareness of typical alternatives triggered by negative expressions. (c) 2024 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
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页数:26
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