The Covid-19 Social Relief of Distress Grant in South Africa: Exploring the Familial and Household Implications of a Datafied Social Protection Cash-Transfer Programme

Datafication of social protection programmes converts beneficiary populations into machine readable data. Given the novelty of the phenomenon there is a subsequent gap in the literature that explores the implications of datafication through real-world social protection programmes. Lacking even more so are studies which explore how datafied social protection programmes affect social structures and everyday lives. Drawing on the implementation of The Covid-19 Social Relief of Distress Grant, South Africa’s first online and automated cash- transfer, and first cash-transfer to benefit able-bodied, working aged and unemployed people, this paper makes two contributions. First, it explores the significance of datafied social protection cash transfers in the everyday lives of potential beneficiaries and their families. Second, it evaluates the suitability of Heeks & Shekhar (2019) systematic and comprehensive data justice framework for datafied social protection cash-transfer programmes from the perspective of beneficiaries. This paper is based on qualitative longitudinal fieldwork with 41 participants during and after the Covid-19 pandemic in urban and rural areas of South Africa. Findings show that given the significance of contextual barriers, families and households living in poverty played an important role in supporting cash transfer beneficiaries, when overcoming data related barriers, to secure their benefit by investing limited shared resources. In the context of a datafied social protection cash- transfer programme in the Global South, families and households are significant mediating factors of structural determinants that affect the outcome of beneficiary entitlements.