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Prevost, Jean-Guy (2019)In: Prutsch, Markus (ed.), Science, Numbers and Politics. Cham: Palgrave Macmillan, pp. 153-180ABSTRACT“The issue of scientific and professional independence is a central concern of National Statistical Offices (NSOs). It pertains not only to scientific and methodological dimensions, such as definition of concepts, or design of surveys and questionnaires, but also to issues such as data release policies, definition of the overall statistical program, nomination or dismissal of the chief statistician, an NSO’s position within government architecture, as well as budgetary discretion. Independence is now an explicit feature of statistical acts and codes of practice in many countries and appears as a condition for securing the public’s trust. After describing the range of formal and informal means developed for protecting statistics independence in OECD countries, this chapter sketches three interpretations of the independence drive: the principal-agent, the independent expert and the technocrat-guardian models.”EXCERPT“But many official statisticians believe that it should extend to more general operational issues, such as data release policies and the definition of the overall statistical program, to organizational or structural dimensions like the nomination or dismissal of the chief statistician or a national statistical office’s (NSO) position within the overall government architecture, or even to fixing the size of an NSO’s budget or at least allowing discretion over its management. The reasons for independence put forward by NSOs and their officials are often presented as self-evident and unproblematic: without perceived independence, public trust would vanish, as would, in consequence, good, “evidence-based” policy. This claim for independence, however, can itself be seen as an instance of the politics of quantification, a crossroads where contending interests and values meet, and as a statistical policy characteristic of the era of neo-liberalism. Following Desrosières, it may indeed be argued that a significant change occurred in official statistics around the 1980s and 1990s, with the shift from a Keynesian orientation to a regime more attuned to the neo-liberal context.” (p. 156f)