More or Less Unnatural: Semantic Similarity Shapes the Learnability and Cross-Linguistic Distribution of Unnatural Syncretism in Morphological Paradigms.

Q1 Social Sciences Open Mind Pub Date : 2022-10-30 eCollection Date: 2022-01-01 DOI:10.1162/opmi_a_00062
Carmen Saldana, Borja Herce, Balthasar Bickel
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Abstract

Morphological systems often reuse the same forms in different functions, creating what is known as syncretism. While syncretism varies greatly, certain cross-linguistic tendencies are apparent. Patterns where all syncretic forms share a morphological feature value (e.g., first person, or plural number) are most common cross-linguistically, and this preference is mirrored in results from learning experiments. While this suggests a general bias towards natural (featurally homogeneous) over unnatural (featurally heterogeneous) patterns, little is yet known about gradients in learnability and distributions of different kinds of unnatural patterns. In this paper we assess apparent cross-linguistic asymmetries between different types of unnatural patterns in person-number verbal agreement paradigms and test their learnability in an artificial language learning experiment. We find that the cross-linguistic recurrence of unnatural patterns of syncretism in person-number paradigms is proportional to the amount of shared feature values (i.e., semantic similarity) amongst the syncretic forms. Our experimental results further suggest that the learnability of syncretic patterns also mirrors the paradigm's degree of feature-value similarity. We propose that this gradient in learnability reflects a general bias towards similarity-based structure in morphological learning, which previous literature has shown to play a crucial role in word learning as well as in category and concept learning more generally. Rather than a dichotomous natural/unnatural distinction, our results thus support a more nuanced view of (un)naturalness in morphological paradigms and suggest that a preference for similarity-based structure during language learning might shape the worldwide transmission and typological distribution of patterns of syncretism.

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或多或少的不自然:语义相似性决定了非自然同步性在词形范式中的可学性和跨语言分布。
语法系统经常在不同的功能中重复使用相同的形式,这就是所谓的同构现象。虽然同义现象千差万别,但某些跨语言倾向是显而易见的。在跨语言中,所有合成词形式共享一个形态特征值(如第一人称或复数)的模式最为常见,这种偏好也反映在学习实验的结果中。虽然这表明自然形态(特征同质)普遍比非自然形态(特征异质)更受欢迎,但人们对不同种类的非自然形态的可学性梯度和分布却知之甚少。在本文中,我们评估了人-数口头协议范式中不同类型非自然模式之间明显的跨语言不对称现象,并在人工语言学习实验中测试了它们的可学性。我们发现,在人称数字范式中,非自然合成模式的跨语言重复出现与合成形式之间共享特征值(即语义相似性)的数量成正比。我们的实验结果进一步表明,合成模式的可学习性也反映了范式的特征值相似程度。我们认为,这种可学性梯度反映了在形态学习中对基于相似性的结构的普遍偏好,而以往的文献表明,这种偏好在词汇学习以及更广泛的类别和概念学习中起着至关重要的作用。因此,我们的研究结果支持对形态学范式中的(非)自然性进行更细致入微的观察,而不是对自然/不自然进行二分法的区分,并表明在语言学习过程中对基于相似性的结构的偏好可能会影响同义词模式在世界范围内的传播和类型分布。
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来源期刊
Open Mind
Open Mind Social Sciences-Linguistics and Language
CiteScore
3.20
自引率
0.00%
发文量
15
审稿时长
53 weeks
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