Abstract
The article describes the emergence and development of positive epistemology and quantification tools in the dynamics of inequalities in education. It contributes to a history of the present at a time when datafication and experimentalism are reappearing in educational policies to justify the reduction of inequalities across international surveys and randomised controlled trials. This socio‐history of metrics also sheds light on transformations about relationships historically established between the welfare state and education that have shaped the representation of inequalities and social programs in education. The use of large‐scale surveys and controlled experiments in social and educational policies developed in the 1920s and 30s, even if their methods and techniques have become more sophisticated due to statistical progress. However, statistical reasoning is today no less persuasive in justifying the measurement of student skills and various forms of state intervention for “at‐risk” children and youth. With the rise of international organisations, notably the European Commission, demographic issues related to school population and the reduction of inequalities have shifted. It is less a question of selecting the most talented or gifted among working‐class students than of investing in human capital from early childhood to improve the education systems’ performance and competitiveness for the lifelong learning economy and European social investment strategy. This article attempts to illustrate this new arithmetic of inequalities in education at the European level.
Highlights
Through several chronological tables, Desrosières (1998, 2002) and Thévenot (2016) showed how statistical thought defines a way of thinking simultaneously the society, modalities of action within it, and its modes of description
Inspired by Desrosières and Thévenot, our arti‐ cle is based on research carried out by historians in Social Inclusion, 2021, Volume 9, Issue 3, Pages 361–371 social sciences and statistics, and discourse analysis based on materials produced by international organisa‐ tions that show how metrics have guided social policies in governing population with major consequences in knowing and measuring inequalities (Dolowitz et al, 2020; Foucault, 2002; Miller & Rose, 2008)
We propose here to char‐ acterise some important historical moments in the inven‐ tion of governing sciences that characterise stable and durable links between the welfare state, education, and metrics of inequalities, even if these relations are called upon to be transformed
Summary
Through several chronological tables, Desrosières (1998, 2002) and Thévenot (2016) showed how statistical thought defines a way of thinking simultaneously the society, modalities of action within it, and its modes of description. By moving away from social work, and by claiming to become an objective science like psychology, sociology asserted itself as a governing science, capable of guiding social poli‐ cies This trend was confirmed in the 1960s with the launch of anti‐poverty programs, which were supported by large‐scale surveys on inequalities in education, partic‐ ularly the one launched by Tyler (1966) for the Johnson‐ Kennedy administration (the forerunner of the National Assessment of Educational Progress) and another by Coleman et al (1966), which had a great impact on com‐ pensatory education policies in the US. Niques by compiling voluminous data on populations Orthodox eugenicists such as Pearson advocated the principles of natural selection and the strict applica‐ tion of biological laws, but natalists were more in favour of extending social legislation to protect children and to develop new institutions (guidance clinics, nurs‐ ery schools, day‐care centres). It served as a landmark for human capi‐ tal economists to improve their methods and analytical models through experimentalism
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