Would a focus on ‘knowledge ecology’ provide a useful alternative to ‘knowledge integration’ in inter- and trans-disciplinary research?
My experience in bringing perspectives from the humanities, arts and social sciences (HASS) to projects led by researchers from science, technology, engineering and mathematics (STEM) has led me to agree with Sharp and colleagues (2011) that ‘knowledge integration’ is essentially a positivist concept, dependent on the idealist model of a unified field of scientific knowledge to which every bit of science contributed.
How can we resolve debates about participatory processes between proponents and skeptics? What role can participatory modelling play in improving participatory processes?
Proponents argue for the merits of participatory processes, which include learning; co-production of knowledge; development of shared understanding of a problem and shared goals; creation of trust; and local power and ownership of a problem.
Sceptics point to evidence of inefficient, time-consuming, participatory processes that escalate conflict and mistrust. They also highlight democratic problems; lack of transparency; and powerful actors that benefit in relation to weaker ones such as the unorganized, poor, and uneducated.
What is an analogy? How can analogies be used to work productively across disciplines in teams?
We know from the pioneering work of Kevin Dunbar (1995), in studying molecular biology labs, that analogies were a key factor in why multidisciplinary labs were much more successful than labs composed of many researchers from the same backgrounds. What is it about analogies that assists multi- and interdisciplinary work?
Integration lies at the heart of inter- and transdisciplinarity. Klein & Newell (1996) call it the “acid test” of interdisciplinarity, and Pohl, van Kerkhoff, Hirsch Hadorn, & Bammer (2008) consider it “the core methodology underpinning the transdisciplinary research process.”
What exactly, though, is integration?
This blog post answers that question while identifying key resources.
The first empirical support for a long-standing complaint by interdisciplinary researchers was recently published in the leading journal Nature. The Australian National University’s Lindell Bromham, Russell Dinnage and Xia Hua showed that interdisciplinary research is less likely to be funded than discipline-based research proposals (Nature, 534, 684–687 (30 June), DOI: 10.1038/nature18315).
They cleverly applied a technique from evolutionary biology that examines relatedness between biological lineages, using a hierarchical classification of research fields rather than an evolutionary tree. The relative representation of different field of research codes and their degree of difference were used as a proxy measure for interdisciplinarity.
The results, based on 5 years of data from the Australian Research Council’s Discovery program, are robust and are unaffected when number of collaborators, primary research field and type of institution are taken into account.
What does it mean to include ‘a social scientist’ in a team tackling complex problems? Here I focus on complex environmental problems and how biophysical and social scientists work together. I’m curious if social scientists face the same issues in other problem areas, such as health.
Things have improved since my early academic career, when I was often asked to justify why a social scientist deserved a seat at the table when discussing environmental questions. It seemed that even supportive natural scientists were motivated to engage their social science colleagues only to ‘fix’ some type of problem caused by people (e.g., politicians, decision-makers, managers, the “general public”).
While it’s now normal for social scientists to be included, they tend to be lumped together, unlike the biophysical scientists who are differentiated into a range of disciplines with relevant specialization areas.
How can institutions help enhance interdisciplinary team success? We share eight practices we have developed at the National Socio-Environmental Synthesis Center (SESYNC) which was launched in 2011 with funding from the U.S. National Science Foundation.
The center supports newly formed research teams from anywhere in the world to work collaboratively at its facility. The teams synthesize existing theories and data to advance understanding of socio-environmental systems and the ability to solve environmental problems.
Como conseguir que um grupo multidisciplinar integrado por economistas, climatologistas, geógrafos, antropólogos, biólogos, sociólogos, jornalistas, engenheiros químicos, engenheiros ambientais e advogados trabalhe de maneira mais interdisciplinar?
Esse foi o desafio encarado por um projeto de pesquisa sobre as percepções de agricultores familiares de quatro biomas brasileiros (a Amazônia, o Cerrado, o Pantanal e o Semiárido) sobre os impactos que as mudanças climáticas estão tendo nos seus modos de vida. Esse pequenos produtores, com baixa disponibilidade de capital, estão expostos a riscos naturais e socioeconômicos, e são extremadamente vulneráveis aos eventos climáticos extremos.
Um fator chave foi a demarcação do marco teórico do projeto, que incluiu a hipótese de que o sucesso das politicas de adaptação aumenta consideravelmente quando essas políticas se baseiam em um conhecimento de primeira mão das realidades cotidianas e das percepções das populações envolvidas.
O desenho da pesquisa foi guiado por três elementos básicos:
What types of unknowns are tackled in interdisciplinary research? I draw on my experience directing a program of research on the feasibility of prescribing pharmaceutical heroin as a treatment for heroin dependence. Analysis of this case revealed six different types of unknowns:
Are there innovative methods that enable students to frame and confront the complexity of real-world problems in the context of sustainable development? Which learning approaches help students engage with design thinking to understand a particular system, and also to start thinking about responsible solutions? Which approaches enable students to reflect on their own actions, as well as become aware of the importance of diverse stakeholder perspectives and how these play out in real-world contexts?
La modélisation participative cherche à impliquer un groupe de personnes dans la conception et la révision d’un modèle. L’objectif à terme consiste à mieux caractériser les problèmes actuels et imaginer collectivement comment tenter de les résoudre. Dans le domaine de l’environnement en particulier, il apparaît nécessaire que les acteurs concernés se sentent impliqués dans la démarche de modélisation, afin qu’ils puissent exprimer leurs propres points de vue, mais aussi pour mieux s’engager dans des décisions collectives. De ce fait, pour aborder la gestion intégrée des ressources, il est nécessaire de mettre les acteurs au centre des préoccupations de recherche, à la fois lors de la phase la conception du modèle mais aussi pour l’exploration de ces scénarios.
As a community of interdisciplinary practice we need to share our collective knowledge on how funders, researchers and wider research partners can work together for better outcomes to address pressing societal challenges.
Funding interdisciplinary research: improving practices and processes
Seven key challenges to funding interdisciplinary research include:
No agreed criteria defining ‘excellence’ in interdisciplinary research.
Poor agreement of the benefits and costs of interdisciplinary ways of working.
No agreement on how much or what kind of additional funding support is required for interdisciplinary research.
No consensus on terminology.
No clearly delineated college of peers from which to select appropriate reviewers.
