Data-driven models of governance across borders : datafication from the local to the global

This special issue looks closely at contemporary data systems in diverse global contexts and through this set of papers, highlights the struggles we face as we negotiate efficiency and innovation with universal human rights and social inclusion. The studies presented in these essays are situated in...

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Main Authors: Arora, Payal, Stevens, Hallam
Other Authors: School of Humanities
Format: Article
Language:English
Published: 2021
Subjects:
Online Access:https://firstmonday.org/ojs/index.php/fm/article/view/9831
https://hdl.handle.net/10356/146714
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1467142021-03-08T05:00:19Z Data-driven models of governance across borders : datafication from the local to the global Arora, Payal Stevens, Hallam School of Humanities Humanities::History Policy Making Data Regimes This special issue looks closely at contemporary data systems in diverse global contexts and through this set of papers, highlights the struggles we face as we negotiate efficiency and innovation with universal human rights and social inclusion. The studies presented in these essays are situated in diverse models of policy-making, governance, and/or activism across borders. Attention to big data governance in western contexts has tended to highlight how data increases state and corporate surveillance of citizens, affecting rights to privacy. By moving beyond Euro-American borders — to places such as Africa, India, China, and Singapore — we show here how data regimes are motivated and understood on very different terms. 2021-03-08T05:00:19Z 2021-03-08T05:00:19Z 2019 Journal Article Arora, P., & Stevens, H. (2019). Data-driven models of governance across borders : datafication from the local to the global. First Monday, 24(4). doi:10.5210/fm.v24i4.9831 1396-0466 https://firstmonday.org/ojs/index.php/fm/article/view/9831 https://hdl.handle.net/10356/146714 10.5210/fm.v24i4.9831 4 24 en First Monday © 2019, Payal Arora and Hallam Stevens. All Rights Reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Humanities::History
Policy Making
Data Regimes
spellingShingle Humanities::History
Policy Making
Data Regimes
Arora, Payal
Stevens, Hallam
Data-driven models of governance across borders : datafication from the local to the global
description This special issue looks closely at contemporary data systems in diverse global contexts and through this set of papers, highlights the struggles we face as we negotiate efficiency and innovation with universal human rights and social inclusion. The studies presented in these essays are situated in diverse models of policy-making, governance, and/or activism across borders. Attention to big data governance in western contexts has tended to highlight how data increases state and corporate surveillance of citizens, affecting rights to privacy. By moving beyond Euro-American borders — to places such as Africa, India, China, and Singapore — we show here how data regimes are motivated and understood on very different terms.
author2 School of Humanities
author_facet School of Humanities
Arora, Payal
Stevens, Hallam
format Article
author Arora, Payal
Stevens, Hallam
author_sort Arora, Payal
title Data-driven models of governance across borders : datafication from the local to the global
title_short Data-driven models of governance across borders : datafication from the local to the global
title_full Data-driven models of governance across borders : datafication from the local to the global
title_fullStr Data-driven models of governance across borders : datafication from the local to the global
title_full_unstemmed Data-driven models of governance across borders : datafication from the local to the global
title_sort data-driven models of governance across borders : datafication from the local to the global
publishDate 2021
url https://firstmonday.org/ojs/index.php/fm/article/view/9831
https://hdl.handle.net/10356/146714
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