Abstract
The cybernetic dream of regulatory ‘dashboard control’ has taken off in the German higher education system. Both government regulators and university managers are engaged in the creation of waves of increasingly fine-grained quantitative data. Yet a wide range of recent case studies of the German higher education sector attest that in spite of this ‘datafication’ frenzy, the impact of the collected data mass on regulatory and managerial decision-making capacities seems to have remained relatively limited. This article explores why, in spite of the considerable investment in quantitative data infrastructures in the German higher education sector, this did not result in significant overt analytical capacity building. It explores three hypotheses: 1) a legal hypothesis according to which quantification is curbed by legal protections under the <em>Rechtsstaat</em>; 2) a dysfunctionality hypothesis which holds that decision makers reject quantification as a flawed and impracticable pursuit; and 3) an egalitarian federalism hypothesis which argues that Germany’s federal states seek to prevent commensurability to avoid comparison and competition. The article finds that, in spite of its inconspicuousness, quantification indeed does inform various central decision-making processes. However, different legal, political, and relational factors prompt decision makers to engage in a hybrid, tempered and, overall, untransparent application of numerical data.
Highlights
The Shiniest CarThe cybernetic dream of regulatory ‘dashboard control’ has taken off in higher education systems across the world (de Boer, Enders, & Schimank, 2008; Espeland & Sauder, 2016; Hood, James, Peters, & Scott, 2004, Chapter 3)
Issue This article is part of the issue “Quantifying Higher Education: Governing Universities and Academics by Numbers” edited by Maarten Hillebrandt (University of Helsinki, Finland) and Michael Huber (University of Bielefeld, Germany)
Over the past three decades, the sector has engaged in the creation of waves of increasingly fine-grained data, which often takes on a numerical form (Franzen, 2018; Huber & Hillebrandt, 2019; Kleimann, 2016)
Summary
The cybernetic dream of regulatory ‘dashboard control’ has taken off in higher education systems across the world (de Boer, Enders, & Schimank, 2008; Espeland & Sauder, 2016; Hood, James, Peters, & Scott, 2004, Chapter 3). The impact of the collected data mass seems to have remained relatively limited in German higher education. Quantitative data are used for purposes of steering and reaching decisions on such issues as budgeting, research funding, hiring, and programme accreditation (Huber & Hillebrandt, 2019; Kleimann & Hückstädt, 2018; Leibner, 2017; Oberschelp, 2017). The impact of such quantification is largely displaced by pre-existing arrangements This even appears to be the case when such data are allegedly included in decisional procedures. Higher education regulators and managers, for example, generally consider article-level metrics, which have mushroomed over the past decade, too context-specific and complex for decision-making frameworks (Franzen, 2018). This article explores why the ‘shiny Mercedes’ of elaborate quantitative data in the German higher education sector has not resulted in analytical capacity building to the extent that it did elsewhere
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
