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A Semiotic Approach to Social Meaning in Language
IF 1.5 1区 文学 Q2 LINGUISTICS Pub Date : 2025-02-02 DOI: 10.1111/josl.12689
Anna M. Babel
<p>Linguistic awareness is a complex and multi-layered set of processes, existing in different forms of consciousness or knowledge. Social meaning resides in the ways that people perceive linguistic behavior as patterned and predictable, depending on their experience with, stereotypes about, and understanding of different groups. Ample evidence from experimental and ethnographic work indicates that sociolinguistic processes are actively engaged in the interactional construction of meaning. Furthermore, these processes hold material power over the world and how our positions in it are constructed. Theorizing these relationships is key to advancing research on sociolinguistic awareness and control and ultimately to understanding the complex linkages between language and social categorization, as evidenced in the contributions to this thematic issue. To illustrate these points, I present data from the Quechua–Spanish contact zone in Bolivia in which speakers report hearing differences in sounds that were not manipulated by the researchers in an experimental study. Second, I examine a case study in an educational setting in which Latinx students are categorized as English language learners based on racializing discourses and biased assessment tools. Both these examples demonstrate the importance of attending to listeners’ representations of socio + linguistic information, not only that which exists in a measurable way “in the world,” but that which is filled in by social expectation and pattern recognition at a sociocognitive level. I draw on semiotic theory, in particular the device of the <i>interpretant</i>, to argue that social information is perceived in dynamic and varied ways as part of the sign system that constitutes language. It is not something that is added on or filtered <i>after</i> linguistic information; indeed, the whole concept of “social vs. linguistic” is a false dichotomy that has led too many researchers astray. The interpretant incorporates elements of our theory of the world in our interpretation of signs and provides a third “leg” to the dualistic Saussurean sign–symbol relationship. That is, our perception of the relationship between sign and symbol is itself part of the sign. This recursive relationship helps us to access the sophisticated systems of social behavior and modeling that people contain and have knowledge of, information that not only assists them in interpreting but also plays a role in constructing meaning and content of socially laden signs. Social meaning resides in the ways that people perceive linguistic behavior as patterned and predictable, yet also dynamic and available for creative play. We cannot rely only on people's experience with, stereotypes about, and understanding of different groups but must also lean toward models that allow for creativity, innovation, and shifting hierarchies. These processes ultimately have material effects on our world and on the power structures that we inhabit and reprod
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引用次数: 0
Introduction to the Thematic Issue
IF 1.5 1区 文学 Q2 LINGUISTICS Pub Date : 2025-02-02 DOI: 10.1111/josl.12690
Anna M. Babel, Kathryn Campbell-Kibler, Kevin B. McGowan

The topics of awareness and control have been investigated for decades in sociolinguistics, but they have been approached in different ways, both theoretically and methodologically, in different corners of the subdiscipline. This has resulted in confusing and sometimes contradictory terminology, as well as divergent theoretical perspectives on what, exactly, is meant by these terms. As our understanding of the relationships between various social and cognitive systems has become more detailed and sophisticated, it has become increasingly urgent to untangle the overlapping and at times contradictory ways of understanding these concepts. For this reason, this Thematic Series responds to a need for further and more coherent development of the concept of awareness - and for coordination between different subfields of (socio)linguistics as we do so.

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引用次数: 0
Place-Based Accentedness Ratings Do Not Predict Sensitivity to Regional Features
IF 1.5 1区 文学 Q2 LINGUISTICS Pub Date : 2025-02-02 DOI: 10.1111/josl.12691
Kathryn Campbell-Kibler

Discussions of sociolinguistic awareness are often about how patterns observed in one practice (often linguistic production) appear in others (often person perception or metalinguistic commentary). Models like Labov's indicator/marker/stereotype trichotomy force this complexity into a single dimension, due to presupposing a conscious/unconscious distinction unsupported in current cognitive psychology. A more effective approach takes a theoretical step back, asking basic questions about how analogous sociolinguistic meanings relate across activities. In this article, I do so by asking whether explicit verbal reports and speaker evaluations of accentedness in Ohio correlate in strength across individual language users. Such a correlation would suggest a shared representation and/or a shared learning process. A total of 1106 participants listened to Ohio talkers reading word lists of trap, dress, lot, or goose tokens. Participants rated each talker's accentedness, then the accentedness of seven Ohio places. The expected main effects emerged: southern and rural Ohio were most accented, then northern Ohio, and lastly cities and central Ohio. Likewise, the acoustic features influenced talker ratings. Crucially, however, these two effects largely did not interact: those most likely to describe northern (southern) Ohio as accented were no more or less sensitive to northern (southern) vowel features. These results support the small but growing evidence that indexical relationships are learned and used independently across linguistic practices. They also move us further from a unidimensional model of awareness toward an approach where different systems are treated independently.

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引用次数: 0
Existential challenges and interactional sociolinguistics/linguistic ethnography 存在的挑战与互动社会语言学/语言民族学
IF 1.5 1区 文学 Q2 LINGUISTICS Pub Date : 2024-11-10 DOI: 10.1111/josl.12685
Ben Rampton
<p>I am not a specialist in digital communication, and instead I do interactional sociolinguistics and linguistic ethnography (henceforth ‘IS’ and ‘LE’), a syncretic research programme that draws <i>inter alia</i> on linguistic anthropology, conversation analysis and Goffman, usually cross-referring to relevant work in other disciplines (Rampton, <span>2022</span>).<sup>1</sup> IS/LE centres on the careful ethnographic observation, recording and analysis of embodied communication, and it investigates communication's embedding in a layered and interweaving multiplicity of social, cultural and material systems and processes. Depending on the questions and arguments that it is addressing, IS/LE certainly varies both in the forms of semiosis and the systems that it attends to (and I myself have tended to focus on spoken interaction in recreational and educational locales affected by racism, social class and securitisation). But when Helen Kelly-Holmes asks whether artificial intelligence (AI) now departs from ‘the known world for sociolinguistics’, it is a timely opportunity to reflect on the possibilities for—or indeed possibility <i>of</i>—IS/LE.</p><p>Kelly-Holmes speaks of a ‘seismic shift’ in the scholarly universe, citing Jan Blommaert (<span>2017</span>, p. 7), who also advocated ‘an acute eye for change’, saying that ‘reality changes. The bastard changes all the time; society refuses to sit still’ (Blommaert & Van de Aa, <span>2020</span>, p. 6). But Blommaert could also be rather equivocal about the significance of these changes, and elsewhere recommends less spectacular adaptations—‘we have to adjust… [and] what you do needs to be relevant, so don't go for the big recipes’ (2020, p. 6). Not knowing more about AI, I cannot gauge authoritatively the magnitude of its implications for IS/LE, but pursuing Blommaert's more muted second option, I can see several ways in which AI can remain a researchable empirical topic (Rampton, <span>2016</span>, pp. 314–324).</p><p>A lot of this can be studied empirically (Georgakopoulou et al., <span>2020</span>). Yes, these technological developments are likely to stretch IS/LE's methodological repertoire, also warranting the formation of new interdisciplinary collaborations with, for example, different kinds of computer scientist. But digital processes like these are actually drawn into analytical salience by one of IS/LE's foundational preoccupations: ‘algorithmic knowledge and media ideologies are now – alongside other semiotic resources and language ideologies – central in <i>having a voice</i>’ (Maly, <span>2022</span>, p. 15; emphasis added).</p><p>At least two terms figure prominently in this shift, driven by reckonings not only with AI but also with coloniality and the climate emergency (Chakrabarty, <span>2012</span>; Kell & Budach, <span>2024</span>; Pennycook, <span>2018</span>). Post-humanism is one, inter alia proposing a ‘philosophical critique of the Western humanist ideal of the “man o
布raidotti本人也倾向于希望,她利用一种审慎的 "技术癖",期待人工智能技术 "解放甚至超越的潜力"(Braidotti, 2016, pp.16-17)。但在吉尔罗伊看来,"当务之急是,与其关心我们想象中的自己是谁或自己是什么,不如关心在当今的紧急状况下以及在肯定会等待我们的更严峻的环境中,我们能为彼此做些什么"(2019)。这一观点与布罗莫特的观点不谋而合:"每当我怀疑自己在学术上所做工作的重要性时(相信我,这种情况经常发生),回答我的是......活动家、工会人士......学校教师"(布罗莫特 &amp; Van de Aa, 2020, p.6)。同样,自 IS/LE 诞生以来,它就一直以 "手工 "实践参与为导向(如 Gumperz 等人,1979 年)。因此,IS/LE 与其他几种方法一样,是一种综合的社会语言学方法,用于分析不同事物如何在不断发展的当下结合和发展,尽管它不断向新的方向延伸,但我看不到它的价值有任何消失的迹象。这一点很重要,因为除了研究之外,这种方法的持续可信性还体现在凯利-霍姆斯提出的紧迫问题的另一个重要场合--我们的教学中,在教学中,人工智能已经在推动一场意义深远的反思(鲁道夫等人,2023;温盖特等人,2024)、鉴于人工智能可以如此流畅地写出一篇文章,论文作为给学生评分的方式现在看来已经死了(除非回到纸笔考试的考场),而语音学、功能语法或会话分析等技术方面的培训现在可能不那么需要关注了,因为正如凯利-霍姆斯的论文中 "聊天 "淡淡地说的那样,人工智能可以做越来越多的分析工作。当然,让学生了解不同框架中的基本理论和方法仍然很重要,当不同的框架结合起来分析具体的交际实践条块时(如在 IS/LE 中),这一点可能最为明显(在课堂上,数据课程非常适合探索它们的不同承受能力(Rampton &amp; Van de Putte:第 7 节)。但是,教学的重中之重是说服学生关心我们课程中涉及的问题空间,激励学生真正参与到学习中来,慢慢地、深思熟虑地、反思性地、经常协作性地沉浸到论点、经验、理论、方法和数据中5 。但是,人工智能的灵活性也要求关注学生所在的机构环境。许多学生通过兼职来维持生活,作业多而时间少,将任务交给人工智能的压力会越来越大。因此,我们需要为学生腾出空间,让他们自己去体验、讨论、阅读和思考,确保我们不会过度教学和评估,即使这需要与新自由主义学院的一些绩效和审计压力作斗争(佩里,2023 年)。即便如此,在实际研究中,IS/LE 也不是一个 "大配方"。但是,只要有体现人类交流的地方,它(以及类似的工作)仍然可以成为一种有用的 "成分":揭示被忽视的交流资源和隐藏的浪费,以不可预知的方式与其他观点进行对话,与学生一起探索本地实践和手头事物对更广泛问题的启示。
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引用次数: 0
Artificial intelligence and the future of sociolinguistic research: An African contextual review 人工智能与社会语言学研究的未来:非洲背景综述
IF 1.5 1区 文学 Q2 LINGUISTICS Pub Date : 2024-11-10 DOI: 10.1111/josl.12679
Patience Afrakoma hMensa
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引用次数: 0
Language is not a data set—Why overcoming ideologies of dataism is more important than ever in the age of AI 语言不是数据集--为什么在人工智能时代,克服数据主义的意识形态比以往任何时候都更重要?
IF 1.5 1区 文学 Q2 LINGUISTICS Pub Date : 2024-11-10 DOI: 10.1111/josl.12680
Iker Erdocia, Bettina Migge, Britta Schneider
<p>Helen Kelly-Holmes’ call to explore the implications for sociolinguistics arising from the increased commercially driven digitalization of society is very timely. Like Kelly-Holmes, we share the view that the growing prevalence of online and artificial intelligence (AI) technologies in all aspects of our lives requires a critical assessment of assumptions, approaches, and practices that have grounded sociolinguistic research since its inception. While our discussion confirms Helen's observations, we also urge the development of a general critical attitude toward understanding language as digital data. The starting point for our argument is Helen's claim that there is an erasure of “authentic” languages from public digital spaces, “making it more difficult to gather data on real usage because it would be necessary to rely on public areas and/or negotiate access to these private spaces” (p. 5). For us, her observation brings to the fore that treating language as data has always been problematic. We want to raise two issues: the general epistemological limitations of using digital user data as a representation of language and community, and the consequent need for methods that take seriously the study of language in its social, political, and technological context. We suggest ethnography as a method for understanding what speakers actually do, and an opening of language research to also consider the workings and socio-political embeddings of digital and generative AI language technologies. Our discussion is in the spirit of a joint fruitful and constructive debate.</p><p>Let us start with a general critique of approaching language as “data” that correlates with social groups, which is so far a neglected aspect in the debates surrounding language, sociolinguistics, and AI. Historically, this discussion links to the colonial backgrounds of Western science and linguistics specifically. Colonial or missionary linguistic research (e.g., Deumert & Storch, <span>2020</span>; Errington, <span>2008</span>) demonstrates that dominant Western epistemologies of language and research methods in linguistics were shaped during the period of European colonialism. An important legacy of European colonialism is that it “sought to fundamentally change and reorganize the social and economic order of the societies it colonized, as opposed to satisfy itself with extracting tribute” (Couldry & Mejias, <span>2019</span>, p. 70). Part of this endeavor involved language “development” activities aimed at the goal of Bible translation and turning the colonized into Christian disciples. This was based on constructions of language that are still dominant today. They developed on the grounds of “collecting data” (in colonial times, often from single speakers) and then transforming the human capacity of embodied, interactive and collaborative meaning-making into word lists, grammar books, or dictionaries (e.g., Deumert & Storch, <span>2020</span>; Gal & Irvine,
海伦-凯利-霍尔姆斯(Helen Kelly-Holmes)呼吁探讨商业驱动的社会数字化对社会语言学的影响,这一呼吁非常及时。与凯利-霍尔姆斯一样,我们也认为,随着网络和人工智能(AI)技术在我们生活的方方面面日益普及,我们需要对社会语言学研究自诞生以来的假设、方法和实践进行批判性评估。我们的讨论证实了海伦的观点,同时我们也敦促大家对理解作为数字数据的语言形成一种普遍的批判态度。我们论证的出发点是海伦的主张,即 "正宗 "语言在公共数字空间中被抹去,"这使得收集真实使用情况的数据变得更加困难,因为有必要依靠公共区域和/或通过协商进入这些私人空间"(第 5 页)。对我们来说,她的观点让我们意识到,将语言作为数据处理一直是个问题。我们想提出两个问题:将数字用户数据作为语言和社区代表的一般认识论局限性,以及因此需要认真研究社会、政治和技术背景下的语言的方法。我们建议将人种学作为了解说话者实际行为的一种方法,并将语言研究扩展到对数字和生成式人工智能语言技术的运作和社会政治嵌入的考虑。让我们先对将语言作为与社会群体相关联的 "数据 "的做法进行一般性批判,迄今为止,在围绕语言、社会语言学和人工智能的争论中,这是一个被忽视的方面。从历史上看,这种讨论与西方科学和语言学的殖民背景有关。殖民地或传教士的语言学研究(如 Deumert &amp; Storch, 2020; Errington, 2008)表明,西方占主导地位的语言认识论和语言学研究方法是在欧洲殖民主义时期形成的。欧洲殖民主义的一个重要遗产是,它 "试图从根本上改变和重组其殖民地社会的社会和经济秩序,而不是满足于榨取贡品"(Couldry &amp; Mejias, 2019, p.70)。这种努力的一部分涉及语言 "发展 "活动,目的是翻译《圣经》并将殖民者变成基督教门徒。这些活动的基础是至今仍占主导地位的语言结构。它们是在 "收集数据 "的基础上发展起来的(在殖民地时代,数据往往来自单个说话者),然后将人类体现性、互动性和协作性的意义生成能力转化为词表、语法书或词典(例如,Deumert &amp; Storch, 2020; Gal &amp; Irvine, 2019, Chap.9)。因此,语言学研究的基础是现在所谓的 "数据主义 "意识形态(Bode &amp; Goodlad, 2023)。这就是相信数据代表人类行为。在数字技术时代,这与追踪人类行为以预测并最终塑造社会生活的目标相结合(Rushkoff,2019 年)。数据主义意味着对量化客观性的信念和对数据处理代理的信任等假设。由此产生的日常生活数据化包括从社会生活流中提取信息,将其与想象的社会现实和类别相匹配,并固定这种关系。在语言学方面,将语言理解为从口头实践中收集并转化为文字的数据,导致将语言概念化为指代代码,将语言概念化为 "自然的"、有系统的、结构整齐的给定对象(例如,Pennycook,2004 年)。这些活动的成果归纳为类型学、发展等级以及优化数据提取和分析的方法(批判性讨论见 Deumert &amp; Storch, 2020)。社会语言学是这一传统的一部分。但与旨在通过语言活动将自己的社会想象强加于人的传教士不同,社会语言学家的目标是发现和解释人们如何使用语言,特别是变体,以加深我们对语言及其社会文化嵌入性的理解,并提高人们的意识和反对歧视。早期的研究工作将人们的语言实践归纳为外部定义的、同质化的宏观社会(如年龄、阶级)和结构性语言类别,并从它们之间的统计相关性中得出意义。然而,随着时间的推移,社会语言学也相继对客观化提出了质疑。
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引用次数: 0
(Socio)linguistics and generative AI: Taking the reins as researchers and steering its use toward ethical outcomes (社会)语言学与生成式人工智能:作为研究人员掌握缰绳,引导其使用走向道德结果
IF 1.5 1区 文学 Q2 LINGUISTICS Pub Date : 2024-11-10 DOI: 10.1111/josl.12682
Matt Kessler, J. Elliott Casal
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引用次数: 0
Fairness, Relationship, and Identity Construction in Human–AI Interaction 人机交互中的公平、关系和身份构建
IF 1.5 1区 文学 Q2 LINGUISTICS Pub Date : 2024-11-10 DOI: 10.1111/josl.12687
Jie Dong
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引用次数: 0
Claiming the research expertise on human–GenAI interaction for sociolinguistics 为社会语言学争取人类--基因人工智能互动的研究专长
IF 1.5 1区 文学 Q2 LINGUISTICS Pub Date : 2024-11-10 DOI: 10.1111/josl.12683
Kok-Sing Tang
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引用次数: 0
AI, power and sociolinguistics 人工智能、权力与社会语言学
IF 1.5 1区 文学 Q2 LINGUISTICS Pub Date : 2024-11-10 DOI: 10.1111/josl.12681
Ico Maly
<p>Ico Maly is associate professor Digital Culture Studies (Tilburg University, The Netherlands).</p><p>In her opening essay, Hellen Kelly-Holmes asks herself and us ‘how Artificial intelligence will change the way that sociolinguists carry out research’. Instead of giving a clear-cut answer to that question, I would like to take one step back. Before we can think about the concrete ways sociolinguists can use artificial intelligence (AI), it would not be a luxury to first have a sociolinguistic theory on AI. AI is not a neutral tool, it has its own epistemology, produces specific discourses and changes sociolinguistic environments. I do not pretend to have such a full-blown sociolinguistic theory of AI, but I would like to use this opportunity to give a first preliminary sketch of what such a sociolinguistic theorization of AI could look like.</p><p>Starting with the latter, it strikes me how Kelly-Holmes downplays her own work and states that ‘the writing (of ChatGPT) is substantially more correct than my own rambling’ (Kelly-Holmes, 2024). She is clearly not alone in such an assessment of AI. Most users of ChatGPT are equally impressed. It explains the success of the app among our students, and the world at large. By February 2023, the app had 100 million people using it on a weekly basis. And in 2024, that number would rise to 180 million. ChatGPT is now so omnipresent that we have to understand it as a <i>cultural force</i>.</p><p>The discourses ChatGPT produces are being used in a vast number of fields: journalism, law, academia, marketing, politics and digital culture in general. And more, the app is now also embedded in social media like Instagram. Other companies have their own LLMs implemented in search engines, smartphones and social media platforms. AI generates language and is used to moderate language, to help you search, to give you a more personalized digital experience and much more. AI has become a central social structure (re)producing and policing language. And in that sense it gives direction to discourse and culture.</p><p>It is exactly this success that warrants sociolinguistic attention as it has effects on individuals, society and language. On the most micro-level, understanding the relation between AI-produced language and society warrants studying it as interaction. When we do that, we see that users are entering a specific type of communicative relation with specific communicative norms. One entity—the human—is taking up the role of the one asking for information, placing the other—the AI—system in a position of knowledge. This framing of the AI bot as the producer of knowledge is a cultural format. It is steered by the example prompts on the ChatGPT website, but also by the many social media pages and YouTube videos that are dedicated to developing the ‘correct prompts’. The other side of the interaction—the chatbot—is programmed to respond in particular ways. This specifically programmed relation is inherent in the d
后者利用各种现实生活经验来理解文本,并根据特定语境中词语的具体用法,为话语赋予身份特征和道德判断。人工智能的认识论与人类学习语言的方式不同,缺乏文化理解是关键所在。人工智能的认识论与人类学习语言的方式不同,缺乏对文化的理解是关键所在。LLMs 中的语言是统计意义上的共同出现,而不是深层次的文化含义。由于这种特定的 LLM 本体论和认识论,所使用的数据至关重要。LLM 是在基于互联网的大型数据集上进行训练的,但大型数据集并不意味着平等或多样化。相反,众所周知,这些数据库存在严重偏差,这正是这些模型需要以消除偏差的形式进行 "对齐 "的原因。本德尔等人(2021 年,第 614 页)认为,"从最初参与互联网论坛,到继续留在那里,再到收集和最终过滤训练数据,当前的做法从每一个步骤来看,都在为霸权观点提供特权"。我们现在明白了,凯利-霍姆斯提出的问题比 ChatGPT 提供给我们的要点要重要得多。如果我们思考一下中介和技术在话语生产中的隐蔽性--凯利-霍尔姆斯恰如其分地提出了这个话题--我们不仅遇到了一个研究问题,它还与权力的再生产有着深刻的联系。看不见的东西是无法质疑的。而这正是社会语言学家应该做的,找到质疑人工智能文化权力的方法。这就意味着,我们需要想方设法 "彰显 "人工智能生产和管理的话语所带来的文化影响。从本质上讲,这迫使我们从人工智能再现了哪些声音、哪些声音仍然不可见的角度来分析人工智能。数字语言 "不属于另一个领域,也不应该被当作另一个领域来研究。最后,我想回到凯利-霍姆斯(Kelly Holmes)向 ChatGPT 提出的主要问题:人工智能将如何改变社会语言学家开展研究的方式,并强调 ChatGPT 的答案中哪些是不可见的。ChatGPT 明确关注社会语言学家如何在其研究中使用 "人工智能",但却一次也没有谈到人工智能如何重塑我们研究的领域,这难道不值得注意吗?换句话说,ChatGPT 不仅将社会语言学家对人工智能的使用正常化,还模糊了人工智能作为数字意识形态基础设施的功能,这种基础设施共同构建了语言,进而共同组织了社会。在将人工智能用作研究工具之前,我们应该首先对人工智能进行批判性分析,并建立人工智能的社会语言学理论。我同意凯利-霍尔姆斯的观点,即社会语言学家应首先关注如何让这种 "无形 "的影响变得可见。比起追问什么是 "真正的 "和 "真实的语言",我们更应该关注 "人工智能(再)生产的语言 "在语境中的功能和影响。我们的研究对象不应是 "真实 "与 "非真实",或 "真实 "与 "非真实",而应是人们如何在社会中使用人工智能生成的语言。这就需要关注人类如何使用人工智能生成的语言并与之互动,他们赋予这些语言的意义,以及这对人工智能的意识形态和文化力量有何启示。
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引用次数: 0
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Journal of Sociolinguistics
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