Funding transformative research: 10 key stages

By Flurina Schneider

Flurina Schneider (biography)

How can funding programmes maximize the potential of transformative research that seeks to make a real difference? How can funders support a more hands-on approach to societal challenges such as ecological crises? A group of Swiss transdisciplinary researchers and funding-agency staff identified 10 overlapping stages and their key ingredients. The stages are also described in the figure below.

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Improving transdisciplinary arts-science partnerships

By Tania Leimbach and Keith Armstrong

Tania Leimbach (biography)

Collaborations with scientists have become a major focal point for artists, with many scientists now appreciating the value of building working relationships with artists and projects often going far beyond illustration of scientific concepts to instead forge new collaborative frontiers. What is needed to better “enable” and “situate” arts–science partnerships and support mutual learning?

Our research looked at the facilitation of arts–science partnerships through the investigation of two unique collaborative projects, developed at two geographically distinct sites, initiated by artist Keith Armstrong. One was enacted with an independent arts organisation in regional Australia and the other at a university art gallery in Sydney, Australia.

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Language matters in transdisciplinarity

By Tilo Weber

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Tilo Weber (biography)

Why should transdisciplinarians, in particular, care about multilingualism and what can be done to embrace it?

From a linguist’s point of view, I suggest that, in a globalized world, a one language policy is not only problematic from the point of view of fair power relations and equal participation opportunities, but it also weakens science as a whole by excluding ideas, perspectives, and arguments from being voiced and heard.

When people communicate, more is at stake than mere exchange of information, coordination of activities, and joint problem solving.

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Linking learning and research through transdisciplinary competences

By BinBin Pearce

BinBin Pearce (biography)

What are the objectives of transdisciplinary learning? What are the key competences and how do they relate to both educational goals and transdisciplinary research goals? At Transdisciplinarity Lab (TdLab), our group answered these questions by observing and reflecting upon the six courses at Bachelor’s, Master’s, and PhD levels that we design and teach in the Department of Environmental Systems Science at ETH Zurich, Switzerland.

Six competence fields describe what we hope students can do with the help of our courses. A competence field contains a set of interconnected learning objectives for students. We use these competence fields as the basis for curriculum design.

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Structure matters: Real-world laboratories as a new type of large-scale research infrastructure

By Franziska Stelzer, Uwe Schneidewind, Karoline Augenstein and Matthias Wanner

What are real-world laboratories? How can we best grasp their transformative potential and their relationship to transdisciplinary projects and processes? Real-world laboratories are about more than knowledge integration and temporary interventions. They establish spaces for transformation and reflexive learning and are therefore best thought of as large-scale research infrastructure. How can we best get a handle on the structural dimensions of real-word laboratories?

What are real-world laboratories?

Real-world laboratories are a targeted set-up of a research “infrastructure“ or a “space“ in which scientific actors and actors from civil society cooperate in the joint production of knowledge in order to support a more sustainable development of society.

Although such a laboratory establishes a structure, most discussions about real-world laboratories focus on processes of co-design, co-production and co-evaluation of knowledge, as shown in the figure below. Surprisingly, the structural dimension has received little attention in the growing field of literature.

Overcoming structure as the blind spot

We want to raise awareness of the importance of the structural dimension of real-world laboratories, including physical infrastructure as well as interpretative schemes or social norms, as also shown in the figure below. A real-world laboratory can be understood as a structure for nurturing niche development, or a space for experimentation that interacts (and aims at changing) structural conditions at the regime level.

Apart from this theoretical perspective, we want to add a concrete “infrastructural” perspective, as well as a reflexive note on the role of science and researchers. Giddens’ use of the term ‘structure’ helps to emphasize that scientific activity is always based on rules (eg., rules of proper research and use of methods in different disciplines) and resources (eg., funding, laboratories, libraries).

The two key challenges of real-world laboratories are that:

  1. both scientists and civil society actors are involved in the process of knowledge production; and,
  2. knowledge production takes place in real-world environments instead of scientific laboratories.
Franziska Stelzer (biography)

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Uwe Schneidewind (biography)

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Karoline Augenstein (biography)

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Matthias Wanner (biography)

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Using Ostrom’s social-ecological systems framework to set context for transdisciplinary research: A case study

By Maria Helena Guimarães

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Maria Helena Guimarães (biography)

How can Elinor Ostrom’s social-ecological systems framework help transdisciplinary research? I propose that this framework can provide an understanding of the system in which the transdisciplinary research problem is being co-defined.

Understanding the system is a first step and is necessary for adequate problem framing, engagement of participants, connecting knowledge and structuring the collaboration between researchers and non-academics. It leads to a holistic understanding of the problem or question to be dealt with. It allows the problem framing to start with a fair representation of the issues, values and interests that can influence the research outcomes. It also identifies critical gaps as our case study below illustrates.

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