The division of cognitive labor and the structure of interdisciplinary problems

Abstract

Interdisciplinarity is strongly promoted in science policy across the world. It is seen as a necessary condition for providing practical solutions to many pressing complex problems for which no single disciplinary approach is adequate alone. In this article we model multi- and interdisciplinary research as an instance of collective problem solving. Our goal is to provide a basic representation of this type of problem solving and chart the epistemic benefits and costs of researchers engaging in different forms of cognitive coordination. Our findings suggest that typical forms of interdisciplinary collaboration are unlikely to find optimal solutions to complex problems within short time frames and can lead to methodological conservatism. This provides some grounds for both reflecting on current science policy and envisioning more effective scientific practices with respect to interdisciplinary problem solving.

How to measure Interdisciplinary Research? A `systemic' design for the model of measurement

“…Glanzel and Debackere (2022) refer to this approach as a "cognitive" approach, while Gates et al (2019) calls it "inspirational". Either cases refer to how knowledge reiterates itself as a process of extrapolation of patterns through social actions (Nightingale, 1998;Rousseau et al, 2019;Reijula et al, 2023). In practice, a theoretical definition of interdisciplinarity as cognition implies a process of social recognition of the importance of the referenced ideas and claims: it implies that scientific authors might operate within disciplinary frameworks (e.g.…”

The emergence of computational social science: Intellectual integration or persistent fragmentation?

“…Furthermore, as Campbell (2017) suggested, discipline-based organisation of research is a factor that may work against intellectual integration: the motivational structure of building a career in a particular discipline gives rise to, in effect, ethnocentrism, or 'lumpy' organisation of scientific work wherein efforts get concentrated around disciplines' centres of gravity while large spaces of rarefied research occupy gaps between disciplines (see also Reijula et al 2023). The resulting accumulation of knowledge may manifest fragmentation rather than integration.…”

A Multiverse Analysis on the relationship between interdisciplinary research and scientific impact

“…The first aspect can be captured by Semantic Divergence, while the second by Semantic Diversity. In both cases, the separation of Business from the other clusters makes it an interesting subject for studies of disciplinary atypicality (Aboelela et al, 2007;Davies et al, 2018;Zhou et al, 2022;Reijula et al, 2023).…”