Achieving transformational change

By Steve Waddell

Steve Waddell (biography)

Realizing the Sustainable Development Goals presents probably the most audacious human organizing challenge ever. Their number, global scale, range of issues, timeline, and number of actors involved is surely unparalleled. They require transformational change. But what is transformational change? How does it differ from other forms of change? What’s required to achieve it?

Colleagues and I have created the SDG (Sustainable Development Goals) Transformations Forum to address these questions. In this blog post I first explore three types of change: incremental, reform and transformation, summarized in the figure below.

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Strengthening the ecosystem for effective team science: A case study from University of California, Irvine, USA

By Dan Stokols, Judith S. Olson, Maritza Salazar and Gary M. Olson

Dan Stokols (biography)

How can an ecosystem approach help in understanding and improving team science? How can this work in practice?

An Ecosystem Approach

Collaborations among scholars from different fields and their community partners are embedded in a multi-layered ecosystem ranging from micro to macro scales, and from local to more remote regions. Ecosystem levels include:

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Transforming transdisciplinarity: Interweaving the philosophical with the pragmatic to move beyond either/or thinking

By Katie Ross and Cynthia Mitchell

Katie Ross (biography)

Can a dive into the philosophical depths of transdisciplinarity provide an orientation to the fundamental purpose and need for transdisciplinarity?

The earlier philosophers of transdisciplinarity – such as Erich Jantsch (1980), Basarab Nicolescu (2002), and Edgar Morin (2008) – all aim to stretch or transcend the dominant Western paradigm, which arises in part from Aristotle’s rules of good thought. Aristotle’s rules of good thought, or his epistemology, state essentially that to make meaning in the world, we must see in terms of difference; we must make sense in terms of black and white, or dualistic and reductive thinking.

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Twelve ways to kill research translation

By Lewis Atkinson

lewis-atkinson
Lewis Atkinson (biography)

Want to reduce the likelihood that your research will produce policy and practice change? Here are 12 anti-rules to prevent research translation.

Anti-rule #1: ONLY FOCUS ON YOUR PART OF THE PROBLEM. Avoid seeing the problem as a whole to limit the intervention possibilities. Acknowledge the translational “gap” but be ambivalent about who owns it. Contest it with others and perpetuate confusion with a range of definitions for what research translation means.

Anti-rule #2: CLOSE OFF THE FLOW OF INFORMATION AND KNOWLEDGE. Keep a tight lid on who is involved and what knowledge is seen to be relevant. Do not share your data or allow access to your sources of data. Minimise the rate of data exchange within and among various research and non-research partners.

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

By Maria Helena Guimarães

maria-helena-guimaraes
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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Foundations of a translational health sciences doctoral program

By Gaetano R. Lotrecchiano and Paige L. McDonald

gaetano-lotrecchiano
Gaetano R. Lotrecchiano (biography)

How can doctoral studies be developed to include innovation in practice and research, as well as systems and complexity thinking, along with transdisciplinarity? This blog post is based on our work introducing a PhD in Translational Health Sciences at George Washington University in the USA.

Innovation in Practice and Research

We suggest that innovation in practice and research is achieved by the integration of knowledge in three key foundational disciplines:

  • translational research
  • collaboration sciences
  • implementation science (Lotrecchiano et al., 2016).

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

By Jan Kwakkel

jan-kwakkel
Jan Kwakkel (biography)

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

  1. Intrinsic limits to predictability in complex systems.
  2. A variety of stakeholders with different perspectives on what the system is and what problem needs to be solved.
  3. 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.

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Toolkits for transdisciplinary research

By Gabriele Bammer

gabriele-bammer
Gabriele Bammer (biography)

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.

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Good practices in system dynamics modelling

By Sondoss Elsawah and Serena Hamilton

sondoss-elsawah
Sondoss Elsawah (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.

serena-hamilton
Serena Hamilton (biography)

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.

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Scaling up amidst complexity

By Ann Larson

ann-larson
Ann Larson (biography)

How can new or under-utilized healthcare practices be expanded and institutionalized to achieve audacious and diverse global health outcomes, ranging from eliminating polio to reversing the rise in non-communicable diseases? How can complex adaptive systems with diverse components and actors interacting in multiple ways with each other and the external environment best be dealt with? What makes for an effective scale-up effort?

Four in-depth case studies of scale-up efforts were used to explore if there were different pathways to positively change a complex adaptive system.

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Complexity and agent-based modelling

By Richard Taylor and John Forrester

richard-taylor
Richard Taylor (biography)

Policy problems are complex and – while sometimes simple solutions can work – complexity tools and complexity thinking have a major part to play in planning effective policy responses. What is ‘complexity’ and what does ‘complexity science’ do? How can agent-based modelling help address the complexity of environment and development policy issues?

Complexity

At the most obvious level, one can take complexity to mean all systems that are not simple, by which we mean that they can be influenced but not controlled. Complexity can be examined through complexity science and complex system models.

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Critical Back-Casting

By Gerald Midgley

gerald-midgley
Gerald Midgley (biography)

How can we design new services or strategies when the participation of marginalized stakeholders is vital to ethicality? How can we liberate people’s creativity so we can move from incremental improvements to more fundamental change?

To answer these questions, I have brought together insights from Russ Ackoff and Werner Ulrich to develop a new method that I call Critical Back-Casting.

Russ Ackoff, writing in the 1980s, is critical of organizations that focus on incremental improvements without ever asking whether they are doing the right thing in the first place. Thus, they are at risk of continually ‘improving’ the wrong thing, when they would be better off going for a more radical redesign. Ackoff makes two far-reaching prescriptions to tackle this problem.

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