山高皇帝远:中国的信用评分和监控资本主义的基础设施

IF 3.2 3区 管理学 Q1 BUSINESS, FINANCE
Ruowen Xu, Yuval Millo, Crawford Spence
{"title":"山高皇帝远:中国的信用评分和监控资本主义的基础设施","authors":"Ruowen Xu,&nbsp;Yuval Millo,&nbsp;Crawford Spence","doi":"10.1111/1911-3846.12925","DOIUrl":null,"url":null,"abstract":"<p>Previous research on calculative intermediaries shows how these effectively challenge, distort, and disrupt accounting practices in ways that policy-makers might not anticipate. The promises of surveillance capitalism—with its attendant data architectures, datafication processes, and technological sophistication—are different, supposing more accurate ways of reading individuals and greater calculative certainty overall. Yet there is little empirical research to explore how surveillance capitalism manifests itself at the organizational level, either conceptually or operationally. As a result, it remains uncertain whether such specters of omniscience are as haunting in reality as they appear in theory. We explore these themes by way of an ethnographic study into credit scoring in China, showing how intermediary organizations developed a multiplicity of credit scoring models based on machine learning and big data that differed both from original expectations and from each other. These different “renditions” of credit scoring suggest that the data architectures of surveillance capitalism are just as much subject to challenge and adaptation by intermediary organizations as calculative practices, such as accounting, are in more analog environments.</p>","PeriodicalId":10595,"journal":{"name":"Contemporary Accounting Research","volume":null,"pages":null},"PeriodicalIF":3.2000,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1911-3846.12925","citationCount":"0","resultStr":"{\"title\":\"The mountains are high and the emperor is far away: Credit scoring and the infrastructure of surveillance capitalism in China\",\"authors\":\"Ruowen Xu,&nbsp;Yuval Millo,&nbsp;Crawford Spence\",\"doi\":\"10.1111/1911-3846.12925\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Previous research on calculative intermediaries shows how these effectively challenge, distort, and disrupt accounting practices in ways that policy-makers might not anticipate. The promises of surveillance capitalism—with its attendant data architectures, datafication processes, and technological sophistication—are different, supposing more accurate ways of reading individuals and greater calculative certainty overall. Yet there is little empirical research to explore how surveillance capitalism manifests itself at the organizational level, either conceptually or operationally. As a result, it remains uncertain whether such specters of omniscience are as haunting in reality as they appear in theory. We explore these themes by way of an ethnographic study into credit scoring in China, showing how intermediary organizations developed a multiplicity of credit scoring models based on machine learning and big data that differed both from original expectations and from each other. These different “renditions” of credit scoring suggest that the data architectures of surveillance capitalism are just as much subject to challenge and adaptation by intermediary organizations as calculative practices, such as accounting, are in more analog environments.</p>\",\"PeriodicalId\":10595,\"journal\":{\"name\":\"Contemporary Accounting Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2023-12-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1911-3846.12925\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Contemporary Accounting Research\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/1911-3846.12925\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Contemporary Accounting Research","FirstCategoryId":"91","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/1911-3846.12925","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0

摘要

以往对计算中介的研究表明,这些中介如何以决策者可能无法预料的方式有效地挑战、扭曲和扰乱会计实践。监控资本主义的承诺--以及随之而来的数据架构、数据化过程和技术复杂性--则与此不同,它假定能以更准确的方式解读个人,并在整体上提高计算的确定性。然而,无论是在概念上还是在操作上,很少有实证研究来探讨监控资本主义在组织层面是如何体现的。因此,这种全知全能的幽灵在现实中是否像在理论中出现的那样阴魂不散,仍然是个未知数。我们通过对中国信用评分的人种学研究探讨了这些主题,展示了中介机构如何基于机器学习和大数据开发出多种信用评分模型,这些模型既不同于最初的预期,也彼此不同。信用评分的这些不同 "演绎 "表明,监督资本主义的数据架构与会计等计算实践在更模拟的环境中一样,会受到中介组织的挑战和调整。本文受版权保护,保留所有权利。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The mountains are high and the emperor is far away: Credit scoring and the infrastructure of surveillance capitalism in China

The mountains are high and the emperor is far away: Credit scoring and the infrastructure of surveillance capitalism in China

Previous research on calculative intermediaries shows how these effectively challenge, distort, and disrupt accounting practices in ways that policy-makers might not anticipate. The promises of surveillance capitalism—with its attendant data architectures, datafication processes, and technological sophistication—are different, supposing more accurate ways of reading individuals and greater calculative certainty overall. Yet there is little empirical research to explore how surveillance capitalism manifests itself at the organizational level, either conceptually or operationally. As a result, it remains uncertain whether such specters of omniscience are as haunting in reality as they appear in theory. We explore these themes by way of an ethnographic study into credit scoring in China, showing how intermediary organizations developed a multiplicity of credit scoring models based on machine learning and big data that differed both from original expectations and from each other. These different “renditions” of credit scoring suggest that the data architectures of surveillance capitalism are just as much subject to challenge and adaptation by intermediary organizations as calculative practices, such as accounting, are in more analog environments.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
6.20
自引率
11.10%
发文量
97
期刊介绍: Contemporary Accounting Research (CAR) is the premiere research journal of the Canadian Academic Accounting Association, which publishes leading- edge research that contributes to our understanding of all aspects of accounting"s role within organizations, markets or society. Canadian based, increasingly global in scope, CAR seeks to reflect the geographical and intellectual diversity in accounting research. To accomplish this, CAR will continue to publish in its traditional areas of excellence, while seeking to more fully represent other research streams in its pages, so as to continue and expand its tradition of excellence.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信