Sharing integrated modelling practices – Part 2: How to use “patterns”?

Community member post by Sondoss Elsawah and Joseph Guillaume

Sondoss Elsawah (biography)

In part 1 of our blog posts on why use patterns, we argued for making unstated, tacit knowledge about integrated modelling practices explicit by identifying patterns, which link solutions to specific problems and their context. We emphasised the importance of differentiating the underlying concept of a pattern and a pattern artefact – the specific form in which the pattern is explicitly described. Continue reading

Sharing integrated modelling practices – Part 1: Why use “patterns”?

Community member post by Sondoss Elsawah and Joseph Guillaume

Sondoss Elsawah (biography)

How can modellers share the tacit knowledge that accumulates over years of practice?

In this blog post we introduce the concept of patterns and make the case for why patterns are a good candidate for transmitting the ‘know-how’ knowledge about modelling practices. We address the question of how to use patterns in a second blog post. Continue reading

Complexity and agent-based modelling

Community member post by Richard Taylor and John Forrester

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?


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. 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

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.

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

Unintended consequences of honouring what communities value and aspire to

Community member post by Melissa Robson

Melissa Robson (biography)

It seems simple enough to say that community values and aspirations should be central to informing government decisions that affect them. But simple things can turn out to be complex.

In particular, when research to inform land and water policy was guided by what the community valued and aspired to rather than solely technical considerations, a much broader array of desirable outcomes was considered and the limitations of what science can measure and predict were usefully exposed. Continue reading

Models as ‘interested amateurs’

Community member post by Pete Barbrook-Johnson

Pete Barbrook-Johnson (biography)

How can we improve the often poor interaction and lack of genuine discussions between policy makers, experts, and those affected by policy?

As a social scientist who makes and uses models, an idea from Daniel Dennett’s (2013) book ‘Intuition Pumps and Other Tools for Thinking’ struck a chord with me. Dennett introduces the idea of using lay audiences to aid and improve understanding between experts. Dennett suggests that including lay audiences (which he calls ‘curious nonexperts’) in discussions can entice experts to err on the side of over-explaining their thoughts and positions. When experts are talking only to other experts, Dennett suggests they under-explain, not wanting to insult others or look stupid by going over basic assumptions. This means they can fail to identify areas of disagreement, or to reach consensus, understanding, or conclusions that may be constructive.

For Dennett, the ‘curious nonexperts’ are undergraduate philosophy students, to be included in debates between professors. For me, the book sparked the idea that models could be ‘curious nonexperts’ in policy debates and processes. I prefer and use the term ‘interested amateurs’ over ‘curious nonexperts’, simply because the word ‘amateur’ seems slightly more insulting towards models! Continue reading