Integration and Implementation Insights

Three schools of transformation thinking

June 9, 2021September 5, 2017

By Uwe Schneidewind and Karoline Augenstein

authors_uwe-schneidewind_karoline-augenstein — 1. Uwe Schneidewind (biography)
2. Karoline Augenstein (biography)

‘Transformation’ has become a buzzword in debates about sustainable development. But while the term has become very popular, it is often unclear what is meant exactly by ‘transformation’.

The fuzziness of the concept can be seen as a strength, giving it metaphoric power and facilitating inter- and transdisciplinary cooperation. However, this fuzziness means there is also a danger of the transformation debate being co-opted by powerful actors and used strategically to impede societal change towards more sustainable pathways.

Creating community around the Science of Team Science

April 9, 2026August 31, 2017

By Stephen M. Fiore

How can we create new academic communities? I provide lessons from building the Science of Team Science (SciTS), a rapidly growing cross-disciplinary field of study. SciTS works to build an evidence-base and to develop translational applications to maximize the efficiency and effectiveness of team-based research.

I particularly draw lessons from the recent 8^th annual conference attended by approximately 200 people [Moderator update – In April 2026, an embedded link to the 8^th annual conference in this sentence was no longer available and so the link structure has been left in place but the active link deleted: scienceofteamscience.org/2017-scits-conference]. The conference aimed to:

disseminate the current state of knowledge in the SciTS field along with applications for enhancing team science;
provide opportunities to discuss future directions for advancing SciTS to improve the global scientific enterprise; and,
provide opportunities for interaction amongst a diverse group of stakeholders, including thought leaders in the SciTS field, scientists engaged in team-based research, institutional leaders who promote collaborative research, policymakers, and federal agency representatives.

What can action research and transdisciplinarity learn from each other?

September 10, 2024August 29, 2017

By Danilo R. Streck

danilo-streck — Danilo R. Streck (biography)

A man raises his hand and brings up the following issue: “Our community is constantly affected by terrible floods that not only destroy our houses, but are the cause of sicknesses of our children.” This statement—in the midst of a participatory budget meeting in South Brazil—raised issues concerning the deforestation of riverbanks, the deficient sewage system, contested land ownership and occupation, among others.

Our research group is primarily interested in citizenship education and in supporting it through studying what makes learning possible (pedagogical mediation) within discussions about the allocation of resources for the public budget. Stories like this one remind us of the limits of a simplistic approach to understanding citizenship. In this case, citizenship and citizenship education was clearly related to health, to ecology, to urban planning, to farming, among other fields of acting and knowing.

Action research, broadly understood as collective (self) reflection in action within situations that one wants to change, is intrinsically an exercise of disciplinary transgressions.

Synthesis centers as critical research infrastructure

May 4, 2020August 22, 2017

By Andrew Campbell

When we think of research infrastructure, it is easy to associate astronomers with telescopes, oceanographers with research vessels and physicists with particle accelerators.

But what sort of research infrastructure (if any) do we need in order to do more effective multidisciplinary, interdisciplinary and transdisciplinary research on big, complex, ‘wicked’ challenges like climate change or food security?

Some eminent colleagues and I argue in a new paper (Baron et al., 2017) that the answers include:

Managing deep uncertainty: Exploratory modeling, adaptive plans and joint sense making

April 15, 2022August 15, 2017

By Jan Kwakkel

How can decision making on complex systems come to grips with irreducible, or deep, uncertainty? Such uncertainty has three sources:

Intrinsic limits to predictability in complex systems.
A variety of stakeholders with different perspectives on what the system is and what problem needs to be solved.
Complex systems are generally subject to dynamic change, and can never be completely understood.

Deep uncertainty means that the various parties to a decision do not know or cannot agree on how the system works, how likely various possible future states of the world are, and how important the various outcomes of interest are.

Four best practices for scaling up effective innovations

November 20, 2025August 8, 2017

By Amanda Fixsen, Karen Blase and Dean Fixsen

authors_amanda-fixsen_karen-blase_dean-fixsen — 1. Amanda Fixsen (biography)
2. Karen Blase (biography)
3. Dean Fixsen (biography)

What is involved in effective scaling up of innovations in order to achieve social impact? Here are four best practices, drawn from our experience in scaling up human services innovations and programs for children and families. We also provide definitions of the key terms used.

1. Understand the target audiences

Effectively scaling innovations first requires attention to defining the denominator, or population of interest for the scale-up effort, as well as the numerator, or the number of children and families who are receiving the innovation with fidelity and good outcomes.

2. Purposeful design leads to high-fidelity use

Productive multivocal analysis – Part 2: Achieving epistemological engagement

March 30, 2023August 3, 2017

By Kristine Lund

In a previous blog post I described multivocality – ie., harnessing multiple voices – in interdisciplinary research and how research I was involved in (Suthers et al., 2013) highlighted pitfalls to be avoided. This blog post examines four ways in which epistemological engagement can be achieved. Two of these are positive and two may have both positive and negative aspects, depending on how the collaboration plays out.

Once a team begins analyzing a shared corpus from different perspectives — in our case, it was a corpus of people solving problems together — it’s the comparison of researchers’ respective analyses that can be a motor for productive epistemological encounters between the researchers.

Productive multivocal analysis – Part 1: Avoiding the pitfalls of interdisciplinarity

March 30, 2023August 1, 2017

By Kristine Lund

Many voices are expressed when researchers from different backgrounds come together to work on a new project and it may sound like cacophony. All those voices are competing to be heard. In addition, researchers make different assumptions about people and data and if these assumptions are not brought to light, the project can reach an impasse later on and much time can be wasted.

So how can such multivocality be positive and productive, while avoiding trouble? How can multiple voices be harnessed to not only achieve the project’s goals, but also to make scientific progress?

Toolkits for transdisciplinary research

March 21, 2024July 25, 2017

By Gabriele Bammer

If you want to undertake transdisciplinary research, where can you find relevant concepts and methods? Are there compilations or toolkits that are helpful?

I’ve identified eight relevant toolkits, which are described briefly below and in more detail in the journal GAIA’s Toolkits for Transdisciplinarity series.

One toolkit provides concepts and methods relevant to the full range of transdisciplinary research, while the others cover four key aspects: (i) collaboration, (ii) synthesis of knowledge from relevant disciplines and stakeholders, (iii) thinking systemically, and (iv) making change happen.

Good practices in system dynamics modelling

December 19, 2024July 18, 2017

By Sondoss Elsawah and Serena Hamilton

authors_sondoss-elsawah_serena-hamilton — 1. Sondoss Elsawah (biography)
2. Serena Hamilton (biography)

Too often, lessons about modelling practices are left out of papers, including the ad-hoc decisions, serendipities, and failures incurred through the modelling process. The lack of attention to these details can lead to misperceptions about how the modelling process unfolds.

We are part of a small team that examined five case studies where system dynamics was used to model socio-ecological systems. We had direct and intimate knowledge of the modelling process and outcomes in each case. Based on the lessons from the case studies as well as the collective experience of the team, we compiled the following set of good practices for systems dynamics modelling of complex systems.

Responsive research – simple, right? The AskFuse case study

July 13, 2021July 11, 2017

By Rosemary Rushmer

Researchers are constantly being challenged to demonstrate that their research can make a difference and has impact. Practice and policy partners are similarly challenged to demonstrate that their decisions and activity are informed by the evidence base. It sounds like all we need to do is join the two groups together – simple, right?

In Fuse (the Centre for Translational Research in Public Health, www.fuse.ac.uk) we wanted to do exactly that. We wanted to supply the evidence that end-users said they wanted (supply and demand), and make it easy for them to access and use research evidence.

Yet, we knew that current approaches to supplying evidence (briefs, guidelines, publications) do not work as well as we once thought they did. It needed a re-think…

Bringing the Immunity-to-Change™ process to the scientific community

May 29, 2026July 4, 2017

By Erica Lawlor and Cheryl Vaughan

authors_erica -lawlor_cheryl-vaughan — 1. Erica Lawlor (biography)
2. Cheryl Vaughan (biography)

How can scientists whose careers were formed in an incentive system that cultivates competitive and territorial behaviors be helped to meet the expectations of collaborative research frameworks? A team-based approach that transcends disciplinary boundaries may be a tall order for scientists who “grew up” in a system where funding and promotion are based upon a proven record of individual contributions to a field of research. But that is the direction in which much of science is heading.