How can social network analysis benefit transdisciplinary research?

By Leonhard Späth, Rea Pärli and the RUNRES project team

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1. Leonhard Späth (biography)
2. Rea Pärli (biography)
3. RUNRES Project Team (participants)

Can we observe in a more analytical way how transdisciplinarity “happens”? How useful is social network analysis in transdisciplinary work, especially for uncovering the role of relationship structures? How can transdisciplinary concepts be used to map connections between those involved in transdisciplinary research?

A very brief introduction to social network analysis

Social network analysis is the study of connections between different people or any other social entity involved in the topic under investigation (referred to as actors), as well as the patterns of those connections and the distribution of the ties among actors.

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Give-and-take matrix for transdisciplinary projects

By Michael Stauffacher and Sibylle Studer

authors_michael-stauffacher_sibylle-studer
1. Michael Stauffacher (biography)
2. Sibylle Studer (biography)

Transdisciplinary research projects often have multiple components, including sub-projects that involve co-production with various stakeholders, more standard discipline-based pieces gathering specific understandings of the problem, and investigations into options for transforming the problem situations.

How can the individual parts of transdisciplinary research projects be effectively aligned? How can interactions and integration within the whole research team be improved? What’s needed to make mutual expectations explicit and to identify possibilities for further collaboration?

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Gradients of agreement for democratic decision-making

By Hannah Love

hannah-love
Hannah Love (biography)

How does your team make decisions? Do you vote? Does the loudest voice usually win? Does everyone on the team generally feel heard? Does your team have a charter to provide guidance? Or maybe there is often just silence and the team assumes agreement?

The next time your team makes a decision, here is something new you can try! Kaner (2014) proposes using a gradients of agreement scale. The gradients of agreement, also known as the consensus spectrum, provides an alternative to yes/no decision-making by allowing everyone to mark their response along a continuum, as shown in the figure below.

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How systems thinking enhances systems leadership

By Catherine Hobbs and Gerald Midgley

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1. Catherine Hobbs (biography)
2. Gerald Midgley (biography)

Systems leadership involves organisations, including governments, collaborating to address complex issues and achieve necessary systemic transformations. So, if this is the case, how can systems leadership be helped by systems thinking?

Systems leadership is concerned with facilitating innovation by bringing together a network of organisations. These then collaborate between themselves and with other stakeholders to deliver some kind of service, influence a policy outcome or develop a product that couldn’t have been achieved by any one of the organisations working alone.

Recognising that a network of organisations can achieve something that emerges from their interactions involves a certain amount of implicit systems thinking.

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Responding to unacknowledged disciplinary differences with the Toolbox dialogue method

By Graham Hubbs, Michael O’Rourke, Steven Hecht Orzack

authors_graham-hubbs_michael-orourke_steven-hecht-orzack
1. Graham Hubbs (biography)
2. Michael O’Rourke (biography)
3. Steven Hecht Orzack (biography)

Have you collaborated with people on a complex project and wondered why it is so difficult? Perhaps you’ve asked yourself, “Do my collaborators even conceive of the project and its goals in the way I do?” Projects involving collaborators from different disciplines or professions seem almost ready made to generate this kind of bewilderment. Collaborators on cross-disciplinary projects like these often ask different kinds of questions and pursue different kinds of answers.

This confusion can bedevil cross-disciplinary research. The allure of such research is its promise of solving complex problems by bringing together a variety of perspectives that when combined lead to solutions that any one perspective would fail to find. But combining different disciplinary perspectives also requires undertaking the tasks of translating different technical languages, reconciling different methodological preferences, and coordinating different ways of carving up the world. These tasks are difficult and it’s no wonder that cross-disciplinary research often fails to be truly cross-disciplinary.

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Breaking through disciplinary barriers with practical mapping

By Steven E. Wallis and Bernadette Wright

author_steven-wallis_and_bernadette-wright
1. Steven E. Wallis (biography)
2. Bernadette Wright (biography)

How can practical mapping help develop interdisciplinary knowledge for tackling real-world problems — such as poverty, justice and health — that have many causes? How can it help take into account political, economic, technological and other factors that can worsen or improve the issues?

Maps are useful because they show your surroundings – where things are in relation to each other (and to you). They show the goals we want to achieve and what it takes to get there.

‘Practical mapping’ is a straight-forward approach for using concepts and connections to integrate knowledge across and between disciplines, to support effective action.

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Providing a richer assessment of research influence and impact

By Gabriele Bammer

author - gabriele bammer
Gabriele Bammer (biography)

How can we affirm, value and capitalise on the unique strengths that each individual brings to interdisciplinary and transdisciplinary research? In particular, how can we capture diversity across individuals, as well as the richness and distinctness of each individual’s influence and impact?

In the course of writing ten reflective narratives (nine single-authored and one co-authored), eleven of us stumbled on a technique that we think could have broader utility in assessing influence and impact, especially in research but also in education (Bammer et al., 2019).

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Theory U: A promising journey to embracing unknown unknowns

By Vanesa Weyrauch

author-venesa-weyrauch
Vanesa Weyrauch (biography)

How can we best live in a VUCA (volatile, uncertain, complex and ambiguous) world? How can we shift from a worldview that looks to predict and control what is to be done through plans and strategies to being present and flexible in order to respond effectively as unexpected changes take place? How can we be open to not knowing what will emerge and embrace uncertainty as the opportunity to co-create and learn?

One powerful and promising way forward is Theory U, a change methodology developed by Otto Scharmer and illustrated below. Scharmer introduced the concept of “presencing”—learning from the emerging future. The concept of “presencing” blends “sensing” (feeling the future possibility) and “presence” (the state of being in the present moment). It acknowledges that we don’t know the answers. Staying at the bottom of the U until the best potential future starts emerging requires embracing uncertainty as fertile soil.

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Blackboxing unknown unknowns through vulnerability analysis

By Joseph Guillaume

Author - Joseph Guillaume
Joseph Guillaume (biography)

What’s a productive way to think about undesirable outcomes and how to avoid them, especially in an unpredictable future full of unknown unknowns? Here I describe the technique of vulnerability analysis, which essentially has three steps:

  • Step 1: Identify undesirable outcomes, to be avoided
  • Step 2: Look for conditions that can lead to such outcomes, ie. vulnerabilities
  • Step 3: Manage the system to mitigate or adapt to vulnerable conditions.

The power of vulnerability analysis is that, by starting from outcomes, it avoids making assumptions about what led to the vulnerabilities.

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Designing scenarios to guide robust decisions

By Bonnie McBain

Bonnie McBain (biography)

What makes scenarios useful to decision makers in effectively planning for the future? Here I discuss three aspects of scenarios:

  • goals;
  • design; and,
  • use and defensibility.

Goals of scenarios

Since predicting the future is not possible, it’s important to know that scenarios are not predictions. Instead, scenarios stimulate thinking and conversations about possible futures.

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Agent-based modelling for knowledge synthesis and decision support

By Jen Badham

Jen Badham (biography)

The most familiar models are predictive, such as those used to forecast the weather or plan the economy. However, models have many different uses and different modelling techniques are more or less suitable for specific purposes.

Here I present an example of how a game and a computerised agent-based model have been used for knowledge synthesis and decision support.

The game and model were developed by a team from the Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), a French agricultural research organisation with an international development focus. The issue of interest was land use conflict between crop and cattle farming in the Gnith community in Senegal (D’Aquino et al. 2003).

Agent-based modelling is particularly effective where understanding is more important than prediction. This is because agent-based models can represent the real world in a very natural way, making them more accessible than some other types of models.

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Managing uncertainty in decision making: What can we learn from economics?

By Siobhan Bourke and Emily Lancsar

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1. Siobhan Bourke (biography)
2. Emily Lancsar (biography)

How can researchers interested in complex societal and environmental problems best understand and deal with uncertainty, which is an inherent part of the world in which we live? Accidents happen, governments change, technological innovation occurs making some products and services obsolete, markets boom and inevitably go bust. How can uncertainty be managed when all possible outcomes of an action or decision cannot be known? In particular, are there lessons from the discipline of economics which have broader applicability?

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