Mah, Alice (2017) Environmental justice in the age of big data : challenging toxic blind spots of voice, speed, and expertise. Environmental Sociology, 3 (2). pp. 122-133. doi:10.1080/23251042.2016.1220849 ISSN 2325-1042.

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Abstract

In recent years, grassroots environmental justice activists have increasingly used big data techniques for monitoring, recording, and reporting toxic environmental exposures. Despite the promise of big data for environmental justice, there is a need to address structural barriers to making toxic environmental exposures visible, and to avoid over-relying on new digital methods and techniques as a panacea for problems of voice. The emphasis of real-time analysis in crowdsourced and participatory big data is good at tracking the immediate aftermath of environmental disasters, but it misses slower-burning environmental problems that emerge over time. While big data more generally may have implications for understanding toxic exposure landscapes across different temporal and spatial scales, it is complex, difficult to analyze, and faces significant problems of reliability. There are three key blind spots of the ethos and practice of big data in relation to environmental justice: voice, speed, and expertise. In the context of increasing pressure to embrace new tools and technologies, it is also important to slow down and to reflect on the wider implications of the age of big data.

Item Type:	Journal Article
Subjects:	G Geography. Anthropology. Recreation > GE Environmental Sciences
Divisions:	Faculty of Social Sciences > Sociology
Library of Congress Subject Headings (LCSH):	Environmental justice, Big data, Environmental health
Journal or Publication Title:	Environmental Sociology
Publisher:	Routledge
ISSN:	2325-1042
Official Date:	2017
Dates:	Date Event 2017 Published 5 October 2016 Available 2 August 2016 Accepted 30 November 2016 Submitted
Volume:	3
Number:	2
Page Range:	pp. 122-133
DOI:	10.1080/23251042.2016.1220849
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Open Access (Creative Commons)
Date of first compliant deposit:	7 October 2016
Date of first compliant Open Access:	7 October 2016
Funder:	European Research Council (ERC)
Grant number:	Grant number 639583

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