How Democracies Know: Identification technologies and quantitative analyses of development in Ghana

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Civil registration systems consist of specific arrangements of categorical variables (among others, name and birth date), which in their unique combination determine the distinct identity of a person. As a fundamentally qualitative expression (or non-indicator) of the official recognition of a person’s existence, civil registration is crucial for accessing basic rights, state services and institutions. At the same time, civil registration intimately ties into practices and infrastructures of quantification that count the thus defined individuals, measure them as variously aggregated populations, and ultimately feed into indicators about population dynamics, e.g. in the area of development. Although indicators play a central role in international development practice, the quality and robustness of development data in the context of incompletely documented populations remains insufficiently understood. Using the key indicator "infant mortality" (SDG 3.2) in Ghana as case study, the subproject investigates the relation between recent innovations in the field of identification technologies and the production of key development indicators in the West African country. The point of departure of the investigation is the current, digital "data revolution" of the Ghanaian population data system. With the aim of improving the timeliness and coverage of population data for internationally standardized reporting procedures (IAEG-SDG), Ghanaian policy makers integrate previously isolated, administrative population registers for new, interoperability-based applications. Through the lens of experts, infrastructures and devices involved in this transformation process, the subproject investigates how the new interoperability of data infrastructures allows classifying and, ultimately, quantifying previously inaccessible realms of life for the purpose of monitoring and controlling development dynamics. Using the register data of Ghana’s District Health Information Management System (DHIMS2) as a starting point, the subproject explores how administrative data feed into the production of the key indicator "infant mortality". The subproject traces the data flows across the institutional boundaries of the DHIMS2 and specialized statistical institutions to understand the processes of data editing, transmission, aggregation, visualization, and, ultimately, publication in the form of key development indicators. Within the research group, the subproject thus contributes directly to the understanding of the complex production process of social key indicators