The rise of the reflexive expert? Epistemic, care-ful and instrumental reflexivity in global public policy

Abstract

The production of data and numbers has become the key mechanism of both knowing and governing global public policy. And yet, processes of quantification are inherently paradoxical: from expectations of technocratic rationality and political usability of producing ‘global’ numbers that count for ‘local’ politics and needs to practical limitation of measurement and the necessity to work with ‘good enough’ data. This begs a question – how do these competing epistemic, political and value orders manifest themselves through the work that experts do? In this article, we explore the problem by focussing on reflexivity as a way for experts (primarily those working in key International Organisations) to make sense of and tame the tensions inherent in their work. Through rich qualitative exploration of over 80 semi-structured interviews with experts working in the areas of poverty, education and statistical capacity development, we contribute to debates in the social studies of quantification by arguing that reflexivity is not just a mental process that experts engage in but rather an important resource allowing them to make sense of the contradictions inherent in their work and to mobilise political and ethical considerations in the technocratic process of producing numbers. We identify three types of reflexivity: (1) epistemic reflexivity – regarding the quality of data and its epistemic status as reflecting the reality; (2) care-ful reflexivity – regarding values embedded in data and the duty of care to the populations affected by the measurement and (3) instrumental reflexivity – regarding political rationality and necessary trade-off required to realise political goals. Overall, the article argues that reflexivity becomes an increasingly central expert practice, allowing the transformation of the process of quantification into one of qualification enabling them to attach political attributes and values to data and measurement.