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Governing through big data: An ethnographic exploration of invisible lives in China's digital surveillance of the coronavirus disease 2019 pandemic

INTRODUCTION/BACKGROUND: Since 2020, China has implemented unprecedented digital health surveillance over citizens and residents in response to the coronavirus disease 2019 pandemic. We explore the implementation of Health Code (jiankang ma), a contract-tracing and risk assessment app for coronaviru...

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Autores principales: Zhang, Liyuan, Rafiq, Mohamed Y
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10134151/
https://www.ncbi.nlm.nih.gov/pubmed/37124328
http://dx.doi.org/10.1177/20552076231170689
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author Zhang, Liyuan
Rafiq, Mohamed Y
author_facet Zhang, Liyuan
Rafiq, Mohamed Y
author_sort Zhang, Liyuan
collection PubMed
description INTRODUCTION/BACKGROUND: Since 2020, China has implemented unprecedented digital health surveillance over citizens and residents in response to the coronavirus disease 2019 pandemic. We explore the implementation of Health Code (jiankang ma), a contract-tracing and risk assessment app for coronavirus disease 2019, in China. By engaging with the concept of ‘ocular ethics’, we ask why and how some populations become invisible in China's Health Code surveillance system. METHODS: This study used an ethnographic approach to critically examine the role of digital technology in the coronavirus disease 2019 pandemic governance. Three months of participant observation and 20 interviews were conducted to understand the design of Health Code and the situation of homeless population. RESULTS: We find that China's digital health surveillance during the coronavirus disease 2019 pandemic has failed to cover the homeless population, who either fail to access Health Code or find ways to avoid its mandatory health surveillance. We further summarize four problems resulting in their exclusion, including the loss of ID cards, access to smartphones and phone numbers, problematic design and elastic surveillance, and the neglect of homeless community's precarious living situation. CONCLUSION: Situating our work in the literature on theories of surveillance and anthropology of pandemics, we argue that without recognizing the structural problems embedded in homelessness, a large number of poor and homeless migrants are rendered invisible in this data-driven health surveillance, which further pushes them into social exclusion.
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spelling pubmed-101341512023-04-28 Governing through big data: An ethnographic exploration of invisible lives in China's digital surveillance of the coronavirus disease 2019 pandemic Zhang, Liyuan Rafiq, Mohamed Y Digit Health Qualitative Study INTRODUCTION/BACKGROUND: Since 2020, China has implemented unprecedented digital health surveillance over citizens and residents in response to the coronavirus disease 2019 pandemic. We explore the implementation of Health Code (jiankang ma), a contract-tracing and risk assessment app for coronavirus disease 2019, in China. By engaging with the concept of ‘ocular ethics’, we ask why and how some populations become invisible in China's Health Code surveillance system. METHODS: This study used an ethnographic approach to critically examine the role of digital technology in the coronavirus disease 2019 pandemic governance. Three months of participant observation and 20 interviews were conducted to understand the design of Health Code and the situation of homeless population. RESULTS: We find that China's digital health surveillance during the coronavirus disease 2019 pandemic has failed to cover the homeless population, who either fail to access Health Code or find ways to avoid its mandatory health surveillance. We further summarize four problems resulting in their exclusion, including the loss of ID cards, access to smartphones and phone numbers, problematic design and elastic surveillance, and the neglect of homeless community's precarious living situation. CONCLUSION: Situating our work in the literature on theories of surveillance and anthropology of pandemics, we argue that without recognizing the structural problems embedded in homelessness, a large number of poor and homeless migrants are rendered invisible in this data-driven health surveillance, which further pushes them into social exclusion. SAGE Publications 2023-04-25 /pmc/articles/PMC10134151/ /pubmed/37124328 http://dx.doi.org/10.1177/20552076231170689 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Qualitative Study
Zhang, Liyuan
Rafiq, Mohamed Y
Governing through big data: An ethnographic exploration of invisible lives in China's digital surveillance of the coronavirus disease 2019 pandemic
title Governing through big data: An ethnographic exploration of invisible lives in China's digital surveillance of the coronavirus disease 2019 pandemic
title_full Governing through big data: An ethnographic exploration of invisible lives in China's digital surveillance of the coronavirus disease 2019 pandemic
title_fullStr Governing through big data: An ethnographic exploration of invisible lives in China's digital surveillance of the coronavirus disease 2019 pandemic
title_full_unstemmed Governing through big data: An ethnographic exploration of invisible lives in China's digital surveillance of the coronavirus disease 2019 pandemic
title_short Governing through big data: An ethnographic exploration of invisible lives in China's digital surveillance of the coronavirus disease 2019 pandemic
title_sort governing through big data: an ethnographic exploration of invisible lives in china's digital surveillance of the coronavirus disease 2019 pandemic
topic Qualitative Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10134151/
https://www.ncbi.nlm.nih.gov/pubmed/37124328
http://dx.doi.org/10.1177/20552076231170689
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