The Impact of Inequalities on Data Policies

Favelas Unified Dashboard Case Study

Bibliographic Data

ID12170751
AuthorsElisa Maria Campos (0000-0001-6569-7871, University of Freiburg, corresponding author)
Year2024
Volume42
Issue6
Pages1403-1420
Publication date2024-01-23
Open AccessYes
TypeARTICLE
VenueSocial Science Computer Review (JOURNAL)
Journal identifiersISSN: 0894-4393 • E-ISSN: 1552-8286
PublisherSAGE Publishing (PUBLISHER • US)
DOI10.1177/08944393231225526
OpenAlexW4391130321
LanguageEN
Citations received1
References cited19

Data is the new asset of the current digital revolution. It is heralded as the “new oil” that will transform the world and function as a magic tool for development policies, with great potential to solve global health dilemmas. However, deep societal inequalities give datafication the risk of escalating disparities through data policies instead of solving them. The pandemic unmasked the price to pay for ignoring deep inequalities, helping this research to answer the question: “How did inequalities impact data policies for the Covid-19 pandemic in Brazil?” To investigate this link, the author develops a theoretical model linking the World-historical model of relational inequalities to the capability approach and data colonization theory. This model sustains the analysis of the data collected in 5 months of participant observation in the Covid-19 Favelas Unified Dashboard plus governmental data analysis and semi-structured interviews with data policymakers for Covid-19 in Brazil. As a result, the author demonstrates how inequalities worked as a trap for data policies and argues that data inequalities go beyond the digital divide. Data inequalities skyrocket vulnerability of the poor, increasing contamination rates, and inhibiting development

Dashboard · Data science · Econometrics · Economics · Geography · Inequality · Regional science · Computer Science · COVID-19 epidemiological studies · Mathematics

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