Algorithmic Allocation: Untangling Rival Considerations of Fairness in Research Management

Abstract

Marketization and quantification have become ingrained in academia over the past few decades. The trust in numbers and incentives has led to a proliferation of devices that individualize, induce, benchmark, and rank academic performance. As an instantiation of that trend, this article focuses on the establishment and contestation of ‘algorithmic allocation’ at a Dutch university medical centre. Algorithmic allocation is a form of data-driven automated reasoning that enables university administrators to calculate the overall research budget of a department without engaging in a detailed qualitative assessment of the current content and future potential of its research activities. It consists of a range of quantitative performance indicators covering scientific publications, peer recognition, PhD supervision, and grant acquisition. Drawing on semi-structured interviews, focus groups, and document analysis, we contrast the attempt to build a rationale for algorithmic allocation—citing unfair advantage, competitive achievement, incentives, and exchange—with the attempt to challenge that rationale based on existing epistemic differences between departments. From the specifics of the case, we extrapolate to considerations of epistemic and market fairness that might equally be at stake in other attempts to govern the production of scientific knowledge in a quantitative and market-oriented way.

Editorial: Quantifying Higher Education: Governing Universities and Academics by Numbers

“…The contributions to the thematic issue are clustered around these two themes. The articles by Kandiko Howson and Buckley (2020), Dix, Kaltenbrunner, Tijdink, Valkenburg, and de Rijcke (2020), and Huber (2020) take up aspects of the life cycle theme and offer case studies of quantification in each of the three countries illustrating how governance by numbers is designed, and how the various actors respond to signals of dysfunctionality that emerge over time. The regulatory nexus theme includes articles by Ringel, Brankovic, and Werron (2020), Hillebrandt (2020), and Krüger (2020).…”

“…The contribution of Dix et al (2020) focusses on the Dutch context. Their case consists of research departments within a medical centre which are confronted with a new performance measurement instrument that directly affects their funding situation.…”

Governance by Numbers: A Panopticon Reversed?

“…At the very least, it is an empirical question whether data collected by, for example, academia.edu has any impact on academics' everyday life. Contributions to this thematic issue emphasize this: They show that observers produce numbers without actually using them (Hillebrandt, 2020), that num-bers are produced without an explicit purpose (Kandiko Howson et al, 2020;Krüger, 2020), and that the purpose of observations can be challenged and contested (Dix et al, 2020). A heuristic of panopticism could complement these contributions by raising questions about the disciplining effects of observations that are more open regarding their specific purpose.…”

“…Krüger (2020), Hillebrandt (2020), and Kandiko Howson and Buckley (2020) illustrate how increasingly extensive and elaborate data infrastructures are becoming an end in themselves. The contributions by Dix, Kaltenbrunner, Tijdink, Valkenburg, and de Rijcke (2020) and Huber (2020) show how performance-based budgeting and quality assurance schemes direct universities, departments and researchers toward new objectives. Ringel, Brankovic, and Werron (2020) demonstrate how organizations ensure the ongoing production and promotion of rankings as a numerical observation of higher education institutions.…”