Creating relevant knowledge in transdisciplinary research projects - Coping with inherent tensions

Abstract

Transdisciplinarity aims to address 'grand societal challenges' especially in the sustainability area through realizing 'alternative' ways of knowledge production which integrate societal actors into research. Yet, despite considerable political and scholarly effort and support, the numerous initiatives and programs devoted to produce 'societally relevant knowledge' often yield rather conventional scientific output. For understanding why this is the case, this research investigates how researchers who were engaged in the Austrian research program proVISION made sense of 'societal relevance' and how they made it do-able in practice. The findings suggest rather uniform coping practices for dealing with inherent tensions between different kinds of relevance. Alignment between them could almost exclusively be achieved through quantification and computer modelling, which reinforced a positivistic understanding of relevance. The scarcity of more diverse collective coping strategies is taken as a starting point for developing conclusions for research funding.

Exploring the readiness of publicly funded researchers to practice responsible research and innovation in digital agriculture

“…This aligns with previous research which has found academics and scientists tend to use values such as a commitment to quality, rigour, autonomy and freedom to inform their views on the expected roles and responsibilities of their profession (Degn 2018;Henkel 2005). However, research has highlighted that scientists' also believe that an important part of their role is to demonstrate expertise, and that this is best exemplified by demonstrating excellence in one's specific discipline (Schikowitz 2020), and in the current study, this is where conflicts appeared to arise. Participants discussed how the perceived roles and responsibilities of the scientist are largely shaped by their beliefs around what types of knowledge should drive the research and innovation process, with scientists often favouring scientific knowledge over lay knowledge.…”

Uncertainty in and around biophysical modelling: insights from interdisciplinary research on agricultural digitalization

“…Interdisciplinary integration within a research organization can help to address such problems, but it may still lack practical engagements with the local knowledges and lived experiences of land managers, regulators and policymakers, or local communities. Transdisciplinary approaches are, therefore, required that purposefully include ‘non-academic’ or ‘non-scientific’ participants [ 15 , 91 , 100 ]. In this sense, responsible research should ultimately lead to collaborative problem framing not only among researchers from multiple scientific disciplines but a variety of actors, and their diverse forms of knowledge.…”

“…In the context of simulation modelling, such transdisciplinary approaches are particularly important when modelled information is intended to contribute meaningfully to the development of policy pathways ([ 98 ]; cf. [ 91 ]). Our experiences regarding agricultural digitalization and associated modelling uncertainties support this view.…”

“…[ 13 ]). Attending to models' background settings thus problematizes a reduction of complex sociocultural phenomena solely into scientific conceptions ([ 90 , p. 84]; [ 91 ]). At the same time, considering contextual factors in tandem with direct and indirect uncertainties avoids a misleading bifurcation into scientific and non-scientific aspects.…”

“…Within shorter-term projects, it can be difficult to have such capacity building institutionally recognized and counted towards researchers' traditional performance criteria (e.g. [ 91 ]). It is, therefore, crucial to reflect on these challenges and the underlying logics for interdisciplinarity.…”