What does interdisciplinarity look like in practice: Mapping interdisciplinarity and its limits in the environmental sciences

Abstract

In this paper we take a close look at current interdisciplinary modeling practices in the environmental sciences, and suggest that closer attention needs to be paid to the nature of scientific practices when investigating and planning interdisciplinarity. While interdisciplinarity is often portrayed as a medium of novel and transformative methodological work, current modeling strategies in the environmental sciences are conservative, avoiding methodological conflict, while confining interdisciplinary interactions to a relatively small set of pre-existing modeling frameworks and strategies (a process we call crystallization). We argue that such practices can be rationalized as responses in part to cognitive constraints which restrict interdisciplinary work. We identify four salient integrative modeling strategies in environmental sciences, and argue that this crystallization, while contradicting somewhat the novel goals many have for interdisciplinarity, makes sense when considered in the light of common disciplinary practices and cognitive constraints. These results provide cause to rethink in more concrete methodological terms what interdisciplinarity amounts to, and what kinds of interdisciplinarity are obtainable in the environmental sciences and elsewhere.

Philosophy of science for sustainability science

“…Bayesian network analysis methods; multi-criteria decision analysis methods; integrated assessment modelling) (see Benson and Stephenson 2018) raises important questions regarding the trade-off between epistemic and ethical values (Vezér et al 2018). Although the propagation and standardization of a relatively small number of modelling frameworks or templates have the methodological advantage of facilitating theoretical work and model development (Humphreys 2004;MacLeod and Nagatsu 2018), relying on the same set of models could also embed assumptions that bias outcomes and undermine reliability (Wimsatt 2007). Analogously, focusing on the same set of management models could produce ethical biases, implicitly prioritizing some values over others, often for epistemic reasons, without sufficient ethical justification.…”

Strange bedfellows: Design research and behavioral design

“…While it is generally accepted that a primary criterion for interdisciplinarity is the integration of knowledge from multiple disciplines (Jacobs & Frickel, 2009;Barry, Born & Weszkalnys, 2008;Choi & Pak, 2006), some suggest that achieving true interdisciplinarity requires meeting three additional attributes: application to real-world challenges, a comprehensive perspective, and a fundamentally disruptive element (MacLeod & Nagatsu, 2018).…”

Disentangling the different layers of interdisciplinarity

“…Cognitive difficulties, equally need to be overcome when starting a discussion on epistemic theories and concepts [Ribeiro, 2016;Lattuca, 2003;MacLeod, 2018;Andersen and Wagenknecht, 2013]. MacLeod [2018] andMacLeod andNagatsu [2018] show that the interdependencies between theory, methods, technologies, epistemic values, cognitive structures, tacitly known to define a discipline are essential to solve problems effectively and efficiently. Integration of disciplines involving collaboration and multiple literacies, with different epistemic cultures does not necessarily result in more effective and efficient problem solving with better innovations or novel insights [MacLeod, 2018;Huutoniemi et al, 2010].…”