Transkillery! What skills are needed to be a boundary crosser?

Community member post by Dena Fam, Tanzi Smith and Dana Cordell

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Dena Fam (biography)

What skills and dispositions are required by researchers and practitioners in transdisciplinary research and practice in crossing boundaries, sectors and paradigms?

The insights here come from interviews with 14 internationally recognized transdisciplinary researchers and practitioners, chosen from a diverse range of research and practice-based perspectives.

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Tanzi Smith (biography)

Here we focus on:

1) skills for specific tasks such as facilitation of a meeting, crafting a well-written report, and communicating effectively across disciplines; and,

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Dana Cordell (biography)

2) dispositions, attitudes, orientations and temperaments of an effective researcher/practitioner, i.e., as a way of being.

 

Six categories of skills and dispositions

The core skills and dispositions of an exceptional transdisciplinary researcher/practitioner can be grouped into six categories, illustrated in the figure below. Continue reading

Argument-based tools to account for uncertainty in policy analysis and decision support

Community member post by Sven Ove Hansson and Gertrude Hirsch Hadorn

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Sven Ove Hansson (biography)

Scientific uncertainty creates problems in many fields of public policy. Often, it is not possible to satisfy the high demands on the information input for standard methods of policy analysis such as risk analysis or cost-benefit analysis. For instance, this seems to be the case for long-term projections of regional trends in extreme weather and their impacts.

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Gertrude Hirsch Hadorn (biography)

However, we cannot wait until science knows the probabilities and expected values for each of the policy options. Decision-makers often have good reason to act although such information is missing. Uncertainty does not diminish the need for policy advice to help them determine which option it would be best to go for.

When traditional methods are insufficient or inapplicable, argument-based tools for decision analysis can be applied. Such tools have been developed in philosophy and argumentation theory. They provide decision support on a systematic methodological basis. Continue reading

Enabling co-creation: From learning cycles to aligning values, rules and knowledge

Community member post by Lorrae van Kerkhoff

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Lorrae van Kerkhoff (biography)

How do we improve? In the context of sustainable development, we continually confront the question of how we can develop meaningful and positive actions towards a ‘better’ world (social, ecological, economic outcomes) despite inherent uncertainties about what the future holds.

Co-creation is one concept among several that seek to reorientate us from simplistic, largely linear ideas of progress towards more nuanced, subtle ideas that highlight that there are many different aspects of ‘progress’, and these can be deeply contested and challenging to reconcile. Enabling co-creation, then – or operationalizing it – means finding practical ways to work together, to deal with our different experiences, aspirations and expectations as well as the uncertainties of the future.

Co-creation sits within a learning paradigm that suggests engagement, social and mutual learning, adaptation and flexibility are key to enabling action in the face of uncertainty. But how do we think about learning? Continue reading

Dealing with deep uncertainty: Scenarios

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Laura Schmitt Olabisi (biography)

Community member post by Laura Schmitt Olabisi

What is deep uncertainty? And how can scenarios help deal with it?

Deep uncertainty refers to ‘unknown unknowns’, which simulation models are fundamentally unsuited to address. Any model is a representation of a system, based on what we know about that system. We can’t model something that nobody knows about—so the capabilities of any model (even a participatory model) are bounded by our collective knowledge.

One of the ways we handle unknown unknowns is by using scenarios. Scenarios are stories about the future, meant to guide our decision-making in the present. Continue reading

Uncertainty in participatory modeling – What can we learn from management research?

Community member post by Antonie Jetter

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Antonie Jetter (biography)

I frequently struggle to explain how participatory modeling deals with uncertainty. I found useful guidance in the management literature.

After all, participatory modeling projects and strategic business planning have one commonality – a group of stakeholders and decision-makers aims to understand and ultimately influence a complex system. They do so in the face of great uncertainty that frequently cannot be resolved – at least not within the required time frame. Businesses, for example, have precise data on customer behavior when their accountants report on annual sales. However, by this time, the very precise data is irrelevant because the opportunity to influence the system has passed.

Two key lessons from the management literature deal with the nature of uncertainty and responding to four major types of uncertainty. Continue reading

Making predictions under uncertainty

Community member post by Joseph Guillaume

Joseph Guillaume (biography)

Prediction under uncertainty is typically seen as a daunting task. It conjures up images of clouded crystal balls and mysterious oracles in shadowy temples. In a modelling context, it might raise concerns about conclusions built on doubtful assumptions about the future, or about the difficulty in making sense of the many sources of uncertainty affecting highly complex models.

However, prediction under uncertainty can be made tractable depending on the type of prediction. Here I describe ways of making predictions under uncertainty for testing which conclusion is correct. Suppose, for example, that you want to predict whether objectives will be met. There are two possible conclusions – Yes and No, so prediction in this case involves testing which of these competing conclusions is plausible. Continue reading