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.

中文翻译：

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不平等对数据政策的影响：Favelas 统一仪表板案例研究

数据是当前数字革命的新资产。它被誉为将改变世界的“新石油”，是发展政策的神奇工具，具有解决全球健康困境的巨大潜力。然而，深刻的社会不平等给数据化带来了通过数据政策而不是解决差距扩大差距的风险。此次疫情暴露了忽视严重不平等现象所要付出的代价，有助于这项研究回答以下问题：“不平等现象如何影响巴西 Covid-19 大流行的数据政策？” 为了研究这种联系，作者开发了一个理论模型，将关系不平等的世界历史模型与能力方法和数据殖民理论联系起来。该模型支持对 Covid-19 Favelas 统一仪表板中 5 个月的参与者观察中收集的数据进行分析，加上政府数据分析以及对巴西 Covid-19 数据政策制定者的半结构化访谈。因此，作者展示了不平等如何成为数据政策的陷阱，并认为数据不平等超越了数字鸿沟。数据不平等加剧了穷人的脆弱性，增加了污染率，并抑制了发展。