Datafying anti-poverty programmes

Implications for Data Justice

Bibliographic Data

ID5830153
AuthorsSilvia Masiero (0000-0002-1427-0779, Loughborough University, corresponding author), Soumyo Da, Soumyo Das (International Institute of Information Technology)
Year2019
Volume22
Issue7
Pages916-933
Publication date2019-05-13
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInformation Communication & Society (JOURNAL)
Journal identifiersISSN: 1369-118X • E-ISSN: 1468-4462
PublisherRoutledge (PUBLISHER • GB)
DOI10.1080/1369118x.2019.1575448
OpenAlexW2946326213
LanguageEN
Citations received30
References cited22

This paper seeks to illuminate the significance of datafication for anti-poverty programmes, meaning social protection schemes designed specifically for poor people. The conversion of beneficiary populations into machine-readable data enables two core functions of social protection, those of recognising entitled beneficiaries and assigning entitlements connected to each anti-poverty scheme. Drawing on the incorporation of Aadhaar, India's biometric population database, in the national agenda for social protection, we unpack a techno-rational perspective that crafts datafication as a means to enhance the effectiveness of anti-poverty schemes. Nevertheless, narratives collected in the field show multiple forms of data injustice on recipients, underpinned by Aadhaar's functionality for a shift of the social protection agenda from in-kind subsidies to cash transfers. Based on such narratives the paper introduces a politically embedded view of data, framing datafication as a transformative force that contributes to reforming existing anti-poverty schemes

Beneficiary · Framing (construction · Injustice · Income, Poverty, and Inequality · Microfinance and Financial Inclusion · Poverty, Education, and Child Welfare

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