Learning linguistic diversity: Listeners have race-based linguistic expectations, but only for phonological variation.

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
ACS Applied Electronic Materials Pub Date : 2024-11-01 Epub Date: 2024-03-21 DOI:10.1037/xge0001560
Alexandra M Ryken, Emma Tupper, Drew Weatherhead
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引用次数: 0

Abstract

In three artificial language experiments, we explored the rate at which adults learned associations between linguistic variation and speaker characteristics. Within each of the experiments, we observed that listeners sociolinguistic learning occurred, regardless of whether the speaker characteristic is social (race and sex/gender) or nonsocial (hat wearing), or whether they heard a phonological or morphological variant. However, we found that listener's initial expectations of what social properties were predictive of linguistic variation differed, impacting overall performance. First, participants were much more likely to assume that a phonological variant was predicted by a social property than a nonsocial property (Experiment 1). Most interestingly, participants were more likely to privilege speaker race than sex/gender, but only in the case of a phonological variant (Experiments 2 and 3). The same effect was found in both White and Black participants, though White participants were more likely to correctly articulate which speaker characteristic explained the variation, suggesting that sociolinguistic learning hinges on real-world experiences with language and social diversity. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

学习语言多样性:听者有基于种族的语言期望,但仅限于语音变化。
在三项人工语言实验中,我们探索了成人学习语言变化与说话者特征之间关联的速度。在每个实验中,我们都观察到,无论说话者的特征是社会性的(种族和性别)还是非社会性的(戴帽子),也无论他们听到的是语音还是形态变异,听者都会进行社会语言学习。然而,我们发现,听者最初对哪些社会属性可预测语言变异的预期不同,从而影响了整体表现。首先,与非社会属性相比,参与者更倾向于认为语音变体是由社会属性预测的(实验 1)。最有趣的是,参与者更倾向于认为说话人的种族而非性/性别,但仅限于语音变体的情况(实验 2 和 3)。在白人和黑人参与者中也发现了同样的效果,尽管白人参与者更有可能正确地说出哪种说话者的特征可以解释这种变异,这表明社会语言学的学习取决于语言和社会多样性方面的实际经验。(PsycInfo Database Record (c) 2024 APA, 版权所有)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.20
自引率
4.30%
发文量
567
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