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Feminist counterpublics and media activism in contemporary France 当代法国的女权主义反公众与媒体行动主义
IF 0.7 Q2 Social Sciences Pub Date : 2023-06-05 DOI: 10.1080/1600910x.2023.2220081
J. Pecourt
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引用次数: 0
The touch of the leader: representation and responsiveness in plebiscitary leader democracy 领袖的触碰:公民投票领袖民主的代表性与回应性
IF 0.7 Q2 Social Sciences Pub Date : 2023-06-05 DOI: 10.1080/1600910x.2023.2220086
G. Illés, András Körösényi
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引用次数: 0
The aleatory moment of finance and the structural production of class-based inequality 金融的决定性时刻和基于阶级的不平等的结构性生产
IF 0.7 Q2 Social Sciences Pub Date : 2023-05-24 DOI: 10.1080/1600910x.2023.2214846
Niamh Mulcahy
This article considers the conceptual role that contingency plays in class-based inequality, by examining financial insecurity in the UK following the 2008 financial crisis, austerity, and the COVID-19 pandemic. Drawing on Althusser's aleatory materialism, I counter postmodern and poststructuralist ideas of contingency as a universally disruptive challenge to power and stratification, showing instead how a pervasive sense of uncertainty drives working households into debt and diminishes savings, creating ongoing financial strain or poverty. Using Althusser's concept of the 'encounter', I note how the emergence of consumer finance is historically contingent, but has become normalized in the wage relation. Financial risk, with its potential to yield high rewards for institutional investors and financial firms trading stocks, securities, and assets, amplifies uncertainty that working households face in socially reproducing themselves, because it forces those who draw an income as their main source of wealth to manage the potential risk of loss on an untradeable commodity. The encounter between financial institutions and working households is thus unevenly weighted, with precarious households unable to offload risk in unpredictable times. I connect this aleatory reading of inequality with Althusser's earlier work on contradiction and overdetermination, to understand the implications of stratification on crisis and change.
本文通过考察2008年金融危机、财政紧缩和COVID-19大流行之后英国的金融不安全感,考虑了偶然性在基于阶级的不平等中所起的概念性作用。借鉴阿尔都塞的偶然性唯物主义,我反对后现代主义和后结构主义的偶然性思想,认为它是对权力和分层的普遍破坏性挑战,相反,我展示了普遍存在的不确定性如何驱使工薪家庭负债并减少储蓄,从而造成持续的财政压力或贫困。利用阿尔都塞的“遭遇”概念,我注意到消费金融的出现在历史上是偶然的,但在工资关系中已经变得正常化。金融风险有可能为机构投资者和交易股票、证券和资产的金融公司带来高额回报,但它放大了工薪家庭在社会再生产中面临的不确定性,因为它迫使那些以收入为主要财富来源的人管理不可交易商品的潜在损失风险。因此,金融机构和工薪家庭之间的遭遇是不均衡的,不稳定的家庭无法在不可预测的时期减轻风险。我将这种对不平等的随意解读与阿尔都塞早期关于矛盾和过度决定的著作联系起来,以理解分层对危机和变化的影响。
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引用次数: 0
A science of stereotypes: paranoiac-critical forays within the medium of information 一门关于刻板印象的科学:对信息媒介的偏执狂式批判
IF 0.7 Q2 Social Sciences Pub Date : 2023-05-04 DOI: 10.1080/1600910X.2023.2235634
Fabian Muniesa
ABSTRACT Contemporary cultures of information technology are particularly propitious to the construction and propagation of stereotypes, and, hence, to the cultural critique thereof. Should that critique take at face value the vernaculars of information and behaviour that this culture affords? Or should it attempt at distorting those vernaculars, so to confront from a different angle the latent problem of the stereotype? A number of recent cultural works (in art, poetry and activism) seem to go in that direction. They may connect, in a sense, with the tradition of the ‘paranoiac-critical method’ once formulated by Salvador Dalí, and they provide an interesting testbed for the ‘science of stereotypes’ once imagined by Pierre Klossowski. This hypothesis is examined here, with reference to a number of contemporary illustrations that feed this perspective.
当代信息技术文化特别有利于刻板印象的构建和传播,因此也有利于对其进行文化批判。这种批评是否应该从表面上理解这种文化所提供的信息和行为的白话?还是应该试图扭曲这些方言,从另一个角度来面对刻板印象的潜在问题?最近的一些文化作品(艺术、诗歌和行动主义)似乎都在朝着这个方向发展。在某种意义上,它们可能与萨尔瓦多Dalí提出的“偏执狂批判方法”的传统联系在一起,它们为皮埃尔·克洛索夫斯基(Pierre Klossowski)曾经设想的“刻板印象科学”提供了一个有趣的实验平台。这一假设在这里进行了检验,并参考了一些当代插图来佐证这一观点。
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引用次数: 1
Introduction to thematic section on ‘social theory in an age of machine learning’
IF 0.7 Q2 Social Sciences Pub Date : 2023-05-04 DOI: 10.1080/1600910X.2023.2223395
C. Borch
The proliferation of machine learning (ML) systems, which are algorithmic assemblages designed to extract patterns from data and make predictions, is visibly transforming society and everyday life. OpenAI’s GPT-4 represents the latest development in this field, but even less remarkable ML systems have made significant inroads into important societal domains over the past decades. For instance, scholars have explored the deployment of ML systems in areas such as credit scoring (Kiviat 2019; Rona-Tas 2020), insurance (Cevolini and Esposito 2020), criminal justice (Brayne and Christin 2021), selfdriving cars (Bissell et al. 2020; Stilgoe 2018), social media (Fourcade and Johns 2020), warfare (Scharre 2018), and automated trading (Hansen 2020; Hansen and Borch 2021). A substantial and growing body of literature has examined the societal effects of these systems. Concerns have been raised about their potential biases (Zou and Schiebinger 2018), their contribution to racial and social inequalities (Benjamin 2019; Eubanks 2018; Noble 2018), and their transformative impact on subjectivity, everyday life, and labour markets (Shestakofsky 2017; Wajcman 2019). Scholars have also discussed the opacity of ML systems and the broader epistemological, ethical, and political implications they entail. These discussions have touched on established notions of accountability, expertise, liability, and more (Amoore 2020; Brighenti and Pavoni 2021; Burrell 2016; Coeckelbergh 2020; Collins 2018; Fazi 2020; Pasquale 2020; Svetlova 2021). Simultaneously, there is a growing recognition, partially fuelled by these studies, that the rise of ML may have profound implications for social theory. On one hand, ML’s use as a new methodological tool holds the promise of uncovering patterns in data that could prompt a reevaluation of established concepts used to describe the social world. While this promise may not yet be fully realized, some scholars are optimistic about ML’s potential to generate theories by extracting non-linear patterns in data (Edelmann et al. 2020; Evans and Aceves 2016). On the other hand, the functioning of ML systems necessitates a reconceptualization of human-centered social theory (Airoldi 2022; Borch 2023; Esposito 2017; Yolgörmez 2021). In certain domains, the actionable predictions of ML systems not only inform human decision-making but replace it entirely (Borch and Min 2023). This distinction sets them apart from previous algorithmic systems and raises questions about accountability, control, ethics, liability, and
机器学习(ML)系统是一种旨在从数据中提取模式并进行预测的算法组合,它的激增正在明显地改变社会和日常生活。OpenAI的GPT-4代表了这一领域的最新发展,但在过去的几十年里,即使不那么引人注目的ML系统也在重要的社会领域取得了重大进展。例如,学者们已经探索了ML系统在信用评分等领域的部署(Kiviat 2019;Rona-Tas 2020)、保险(Cevolini and Esposito 2020)、刑事司法(Brayne and Christin 2021)、自动驾驶汽车(Bissell et al. 2020;Stilgoe 2018)、社交媒体(Fourcade and Johns 2020)、战争(Scharre 2018)和自动交易(Hansen 2020;Hansen and Borch 2021)。越来越多的文献研究了这些系统的社会影响。人们对它们的潜在偏见(Zou and Schiebinger 2018)、它们对种族和社会不平等的贡献(Benjamin 2019;尤班克斯2018;Noble 2018),以及它们对主体性、日常生活和劳动力市场的变革性影响(Shestakofsky 2017;Wajcman 2019)。学者们还讨论了机器学习系统的不透明性以及它们所带来的更广泛的认识论、伦理和政治影响。这些讨论触及了既定的问责制、专业知识、责任等概念(Amoore 2020;Brighenti and Pavoni 2021;伯勒尔2016;Coeckelbergh 2020;柯林斯2018;Fazi 2020;帕斯夸里2020;Svetlova 2021)。同时,在这些研究的推动下,越来越多的人认识到,机器学习的兴起可能对社会理论产生深远的影响。一方面,机器学习作为一种新的方法论工具,有望揭示数据中的模式,从而促使人们重新评估用于描述社会世界的既定概念。虽然这一承诺可能尚未完全实现,但一些学者对机器学习通过提取数据中的非线性模式来生成理论的潜力持乐观态度(Edelmann et al. 2020;Evans and Aceves 2016)。另一方面,机器学习系统的功能需要对以人为中心的社会理论进行重新概念化(Airoldi 2022;Borch 2023;埃斯波西托2017;Yolgormez 2021)。在某些领域,机器学习系统的可操作预测不仅为人类决策提供信息,而且完全取代人类决策(Borch和Min 2023)。这种区别使它们与以前的算法系统区别开来,并提出了关于问责制、控制、道德、责任和
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引用次数: 0
The displacement of reality tests. The selection of individuals in the age of machine learning 置换现实检验。
IF 0.7 Q2 Social Sciences Pub Date : 2023-05-04 DOI: 10.1080/1600910X.2023.2221398
D. Cardon, Jean-Marie John-Mathews
ABSTRACT This article presents an interpretation of the transformation of selection tests in our societies, such as competitive examinations, recruitment or competitive access to goods or services, based on the opposition between reality and world proposed by Luc Boltanski in On Critique. We would like to explore the change in the format of these selection tests. We argue that this change is made possible by a spectacular enlargement of the space for comparisons between candidates and by the implementation of machine learning techniques. But this shift is not the only and simple consequence of the introduction of the technological innovation brought by massive data and artificial intelligence. It finds justification in the institutions and organizations that order selection tests because this new test format claims to absorb the multiple criticisms that our societies constantly raise against the previous generations of tests. This is why we propose to interpret the attention and the development of these automated procedures as a technocratic response to the development of a critique of the categorical representation of society.
本文以波尔坦斯基在《批判》一书中提出的现实与世界的对立为基础,对我们社会中竞争性考试、招聘或竞争获取商品或服务等选择测试的转变进行了解释。我们想探讨这些选择测试格式的变化。我们认为,这种变化是通过显著扩大候选人之间的比较空间和实现机器学习技术而实现的。但这种转变并不是引入海量数据和人工智能带来的技术创新的唯一和简单的结果。它在安排选拔考试的机构和组织中找到了理由,因为这种新的考试形式声称吸收了我们的社会不断对前几代考试提出的多种批评。这就是为什么我们建议将这些自动化程序的关注和发展解释为技术官僚对社会分类表征批判发展的回应。
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引用次数: 2
Introduction. Political arithmetic: old and new 介绍。政治算术:旧的和新的
IF 0.7 Q2 Social Sciences Pub Date : 2023-05-04 DOI: 10.1080/1600910X.2023.2243658
S. Day, Celia Lury, H. Ward
ABSTRACT The articles in this Special Issue arose from a workshop in June 2021 (https://peoplelikeyou.ac.uk/activities/people-like-you-a-new-political-arithmetic/) which considered whether we might understand the enormous variety of calculations we encounter today as a political arithmetic. Our proposal was that the term provides a powerful way to understand the political nature of calculations of economic and social value. In this introduction we showcase how contributors address the proposal in studies of personalisation, competitive test formats, algorithmic profiling, YouTube personalities and the significance of information as an increasingly important medium of ‘the social. We suggest that, together, these developments are transforming relations between the individual and society today in ways that both intensify inequalities and provide the basis for new forms of individual and collective identity.
本期特刊中的文章源于2021年6月的一个研讨会(https://peoplelikeyou.ac.uk/activities/people-like-you-a-new-political-arithmetic/),该研讨会讨论了我们是否可以将我们今天遇到的各种各样的计算理解为政治计算。我们的建议是,这个术语提供了一种强有力的方式来理解经济和社会价值计算的政治本质。在本导论中,我们将展示贡献者如何在个性化、竞争性测试格式、算法分析、YouTube个性以及信息作为“社会”日益重要的媒介的重要性的研究中解决该提案。我们认为,这些发展共同改变了今天个人与社会之间的关系,既加剧了不平等,又为个人和集体的新形式提供了基础。
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引用次数: 0
Some-any: approximating personalization in contemporary ensembles Some-any:在当代合奏中近似个性化
IF 0.7 Q2 Social Sciences Pub Date : 2023-03-21 DOI: 10.1080/1600910X.2023.2185874
A. Mackenzie
ABSTRACT The paper situates personalization by comparing widely used numbering practices on social media and other digital platforms. It draws on A.N. Whitehead's analysis of approximation to identify how probabilities and hashes, two key approximating practices, combine to configure platforms and individual users. It shows how personalization in a typical social media setting, the Instagram Explore Page, both distributes individual differences in a statistical manifold and indexes a state of affairs of persons, things, transactions, times and places in numbers such as hashes. Approaching personalization as a practice of entangled approximations, I suggest, shows how relational mappings developed by social media platform overflow the cultural-economic logic of targetted advertising. I argue that the combination of probabilities and hashes, or statistical manifolds and distributed coordination practices, articulate new versions of the some-any relationships embedded in many facets of social life. As approximations, these numberings point to the possibility of new critical framings of technical ensembles and their capacity to condition the formation of groups.
本文通过比较社交媒体和其他数字平台上广泛使用的编号实践来定位个性化。它借鉴了A.N.怀特黑德(A.N. Whitehead)对近似的分析,以确定概率和哈希这两种关键的近似实践如何结合起来配置平台和个人用户。它展示了在典型的社交媒体设置中,即Instagram Explore Page,个性化如何在统计流形中分配个体差异,并以哈希等数字索引人、事、交易、时间和地点的事务状态。我认为,将个性化作为一种纠缠近似的实践,表明了社交媒体平台开发的关系映射如何溢出了定向广告的文化经济逻辑。我认为,概率和哈希的结合,或者统计流形和分布式协调实践的结合,阐明了嵌入社会生活许多方面的某种关系的新版本。作为近似值,这些数字指出了技术整体的新关键框架的可能性以及它们制约群体形成的能力。
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引用次数: 1
Differentiating natures, connecting environments pragmatic sociology and the emergence of green justifications 区分自然、连接环境、实用社会学与绿色理由的出现
IF 0.7 Q2 Social Sciences Pub Date : 2023-03-21 DOI: 10.1080/1600910x.2023.2187736
T. Lehtimäki, M. Virtanen
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引用次数: 1
YouTube personalities as infrastructure: assets, attention choreographies and cohortification processes YouTube个性作为基础设施:资产、注意力编排和协同化过程
IF 0.7 Q2 Social Sciences Pub Date : 2023-03-16 DOI: 10.1080/1600910X.2023.2185873
Emily Rosamond
ABSTRACT YouTube, the world’s most popular online video sharing and social media platform, is filled with personalities. Lifestyle bloggers, hobbyists, self-styled newscasters and exercise instructors add flair to what they share, carving out a niche in a crowded field. Typically, personality is understood as something that belongs to its bearer. But how might it be possible to analyze YouTube, starting from the opposite proposition: that the ‘YouTube personality’ is not so much a property of the persons featured, as it is a property of the platform itself? This article argues that on YouTube, personalities become estranged from their ostensible bearers, becoming platform infrastructure. YouTube not only broadcasts personalities; it renders personalities operational. YouTube personalities act as assetization infrastructure, in that they continually compensate for the poor terms offered on advertising revenue, producing links within ecosystems of opportunities that extend beyond the platform. They also act as cohortification infrastructures, transforming the platform’s surveillance-marketing logic of cohortification – the continuous placement of users into cohorts of similar users – into a participatory process.
YouTube是世界上最受欢迎的在线视频分享和社交媒体平台,它充满了个性。生活方式博主、业余爱好者、自诩的新闻播音员和健身教练为他们的分享增添了一些风格,在拥挤的领域中开辟了一个小众市场。通常,人格被理解为属于其承载者的东西。但是,如何从相反的命题开始分析YouTube呢?即“YouTube个性”与其说是人物的属性,不如说是平台本身的属性。本文认为,在YouTube上,人物与他们表面上的承载者变得疏远,成为平台基础设施。YouTube不仅播放名人;它使人格具有操作性。YouTube名人扮演着资产化基础设施的角色,因为他们不断补偿广告收入所提供的糟糕条款,在平台之外的机会生态系统内建立链接。它们还充当协同基础设施,将平台的协同监控-营销逻辑(将用户持续放置到类似用户的队列中)转变为一个参与过程。
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引用次数: 1
期刊
Distinktion-Journal of Social Theory
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