Drawing on the first comprehensive investigation into the uses of data analytics in UK public services, this article outlines developments and practices surrounding the upsurge in data-driven forms of what we term 'citizen scoring'. This refers to the use of data analytics in government for the purposes of categorisation, assessment and prediction at both individual and population level. Combining Freedom of Information requests and semi-structured interviews with public sector workers and civil society organisations, we detail the practices surrounding these developments and the nature of concerns expressed by different stakeholder groups as a way to elicit the heterogeneity, tensions and negotiations that shape the contemporary landscape of data-driven governance. Described by practitioners as a way to achieve a 'golden view' of populations, we argue that data systems need to be situated in this context in order to understand the wider politics of such a 'view' and the implications this has for state-citizen relations in the scoring society.

This article analyses three distinct child welfare data systems in England. We focus on child welfare as a contested area in public services where data systems are being used to inform decisionmaking and transforming governance. We advance the use of "data assemblage" as an analytical framework to detail how key political and economic factors influence the development of these data systems. We provide an empirically grounded demonstration of why child welfare data systems must not be considered neutral decision aid tools. We identify how systems of thought, ownership structures, policy agendas, organizational practices, and legal frameworks influence these data systems. We find similarities in the move toward greater sharing of sensitive data, but differences in attitudes toward public-private partnerships, rights and uses of prediction. There is a worrying lack of information available about the impacts of these systems on those who are subject to themparticularly in relation to predictive data systems. We argue for policy debates to go beyond technical fixes and privacy concerns to engage with fundamental questions about the power dynamics and rights issues linked to the expansion of data sharing in this sector as well as whether predictive data systems should be used at all.

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T he electrical conductivities o f a n u m b e r o f m etallic long-chain alkyl sulphates h ave been m easured a t different te m p e ra tu re s (L otterm oser and P uschell 1933; H ow ell a n d R obinson 1936).T he curve for each sa lt a t each te m p e ra tu re consists o f th ree distinct ranges.* O ver th e first range th e co n d u ctiv ity falls as a linear function of the square ro o t of th e co n centration. T he b eh av io u r is ty p ic a l o f th a t of a simple electrolyte a n d conform s to th e D ebye-H uckel th e o ry of ionic interaction; th e O nsager slope is only a little g re a ter th a n for a sim ple salt. I t is therefore generally agreed th a t over th is first range th e electrolyte is completely * Compare the curve for silver dodecyl sulphate, fig. 2.