Milan Stefania, Treré Emiliano
University of Amsterdam, The Netherlands.
Cardiff University, UK.
Soc Media Soc. 2020 Aug 11;6(3):2056305120948233. doi: 10.1177/2056305120948233. eCollection 2020 Jul.
Quantification is central to the narration of the COVID-19 pandemic. Numbers determine the existence of the problem and affect our ability to care and contribute to relief efforts. Yet many communities at the margins, including many areas of the Global South, are virtually absent from this number-based narration of the pandemic. This essay builds on critical data studies to warn against the universalization of problems, narratives, and responses to the virus. To this end, it explores two types of data gaps and the corresponding "data poor." The first gap concerns the data poverty perduring in low-income countries and jeopardizing their ability to adequately respond to the pandemic. The second affects vulnerable populations within a variety of geopolitical and socio-political contexts, whereby data poverty constitutes a dangerous form of invisibility which perpetuates various forms of inequality. But, even during the pandemic, the disempowered manage to create innovative forms of solidarity from below that partially mitigate the negative effects of their invisibility.
量化是新冠疫情叙述的核心。数字决定了问题的存在，并影响我们提供护理和参与救援工作的能力。然而，许多处于边缘地位的社区，包括全球南方的许多地区，在这种基于数字的疫情叙述中几乎没有出现。本文基于批判性数据研究，警告不要将问题、叙述和应对病毒的方式普遍化。为此，它探讨了两种类型的数据差距以及相应的“数据贫困”情况。第一个差距涉及低收入国家长期存在的数据贫困问题，这危及它们充分应对疫情的能力。第二个差距影响各种地缘政治和社会政治背景下的弱势群体，数据贫困构成了一种危险的无形形式，使各种形式的不平等长期存在。但是，即使在疫情期间，被剥夺权力者也设法从底层创造出创新的团结形式，部分减轻了他们无形状态的负面影响。
