Decision making – Page 4 – Integration and Implementation Insights

What every interdisciplinarian should know about p values

April 15, 2022April 30, 2019

By Alice Richardson

In interdisciplinary research it’s common for at least some data to be analysed using statistical techniques. Have you been taught to look for ‘p < 0.05’ meaning that there is a less than 5% probability that the finding occurred by chance? Do you look askance at your statistician colleagues when they tell you it’s not so simple? Here’s why you need to believe them.

The whole focus on p < 0.05 to the exclusion of all else is a historical hiccup, based on a throwaway line in a manual for research workers. That manual was produced by none other than R.A. Fisher, giant of statistical inference and inventor of statistical methods ranging from the randomised block design to the analysis of variance. But all he said was that “[p = 0.05] is convenient to take … as a limit in judging whether a deviation is to be considered significant or not.” Convenient, nothing more!

You are biased!

September 11, 2024September 18, 2018

By Matthew Welsh

Complex, real-world problems require cooperation or agreement amongst people of diverse backgrounds and, often, opinions. Our ability to trust in the goodwill of other stakeholders, however, is being eroded by constant accusations of ‘bias’. These are made by commentators about scientists, politicians about media outlets and people of differing political viewpoints about one another. Against this cacophony of accusation, it is worthwhile stepping back and asking “what do we mean when we say ‘bias’ and what does it say about us and about others?”.

Using the concept of risk for transdisciplinary assessment

December 19, 2022March 6, 2018

By Greg Schreiner

Global development aspirations, such as those endorsed within the Sustainable Development Goals, are complex. Sometimes the science is contested, the values are divergent, and the solutions are unclear. How can researchers help stakeholders and policy-makers use credible knowledge for decision-making, which accounts for the full range of trade-off implications?

‘Assessments’ are now commonly used.Following their formal adoption by the Intergovernmental Panel for Climate Change (IPCC) in the early 1990s, they have been used at the science-society-policy interface to tackle global questions relating to biodiversity and ecosystems services, human well-being, ozone depletion, water management, agricultural production, and many more.

Given the nature of the questions they address, assessments are transdisciplinary, involving integration of different knowledge domains. In this piece, I briefly explore what an assessment is and then describe the assessment for shale gas development in South Africa, where we used the concept of risk as the integrative framework.

A new boundary object to promote researcher engagement with policy makers / Un nuevo objeto frontera para promover la colaboración de los investigadores con los tomadores de decisiones

April 15, 2022October 3, 2017

By María D. López Rodríguez

A Spanish version of this post is available

Can boundary objects be designed to help researchers and decision makers to interact more effectively? How can the socio-political setting – which will affect decisions made – be reflected in the boundary objects?

Here I describe a new context-specific boundary object to promote decision making based on scientific evidence. But first I provide a brief introduction to boundary objects.

What is a ‘boundary object’?

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.

Keys to transformation: Interactions of values, rules and knowledge

February 10, 2025June 20, 2017

By Russell Gorddard, Matthew Colloff, Russell Wise and Michael Dunlop

gorddard_colloff_wise_dunlop — 1. Russell Gorddard (biography)
2. Matthew Colloff (biography)
3. Russell Wise (biography)
4. Michael Dunlop (biography)

Adapting to climate change can require profound alterations in environmental management and policy. However the social context of a decision process limits options and resists change, often dooming attempts to adapt to climate change even before they begin. How can decision makers in policy and management more effectively see the institutional and social water they swim in, in order to better drive change?

Values, rules and knowledge (vrk) provide a useful heuristic to help decision makers analyze how the social system shapes their decision context. Put simply, decisions require:

knowledge of options and their implications
values to assess the options
rules that enable implementation.

Looking for patterns: An approach for tackling tough problems

October 9, 2023May 23, 2017

By Scott D. Peckham

What does the word ‘pattern’ mean to you? And how do you use patterns in addressing complex problems?

Patterns are repetitions. These can be in space, such as patterns in textiles and wallpaper, which include houndstooth, herringbone, paisley, plaid, argyle, checkered, striped and polka-dotted.

The pattern concept can also be applied to repetitions in time, as occur in music. Those who know the temporal patterns can classify a piece of music as a blues, waltz or salsa. For each of these types of music, there are also classic dance steps, that usually go by the same name; these are patterns of movement in space and time.

These examples get to the idea that patterns can be viewed more generally as any type of repetitive structure or recurring theme that we can look for and potentially recognize or discover and then assign a memorable name to, such as “houndstooth” or “waltz”.

Scoping: Lessons from environmental impact assessment

April 15, 2022April 4, 2017

By Peter R. Mulvihill

peter-mulvihill — Peter R. Mulvihill (biography)

What can we learn about the role and importance of scoping in the context of environmental impact assessment?

“Closed” versus “open” scoping

I am intrigued by the highly variable approaches to scoping practice in environmental impact assessment and the considerable range between “closed” approaches and more ambitious and open exercises. Closed approaches to scoping tend to narrow the range of questions, possibilities and alternatives that may be considered in environmental impact assessment, while limiting or precluding meaningful public input. Of course, the possibility of more open scoping is sometimes precluded beforehand by narrow terms of reference determined by regulators.

When scoping is not done well, it inevitably compromises subsequent steps in the process.

The path perspective on modelling projects

February 10, 2025March 28, 2017

By Tuomas J. Lahtinen, Joseph H. A. Guillaume, Raimo P. Hämäläinen

authors_tuomas-lahtinen_joseph-guillaume_raimo_hamalainen — 1. Tuomas J. Lahtinen (biography)
2. Joseph H. A. Guillaume (biography)
3. Raimo P. Hämäläinen (biography)

How can we identify and evaluate decision forks in a modelling project; those points where a different decision might lead to a better model?

Although modellers often follow so called best practices, it is not uncommon that a project goes astray. Sometimes we become so embedded in the work that we do not take time to stop and think through options when decision points are reached.

One way of clarifying thinking about this phenomenon is to think of the path followed. The path is the sequence of steps actually taken in developing a model or in a problem solving case. A modelling process can typically be carried out in different ways, which generate different paths that can lead to different outcomes. That is, there can be path dependence in modelling.

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

September 11, 2024February 23, 2017

By Sven Ove Hansson and Gertrude Hirsch Hadorn

authors_sven-ove-hansson_gertrude-hirsch-hadorn — 1. Sven Ove Hansson (biography)
2. Gertrude Hirsch Hadorn (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.

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.

Unintended consequences of honouring what communities value and aspire to

June 19, 2024January 26, 2017

By Melissa Robson

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.

Models as ‘interested amateurs’

September 5, 2024January 24, 2017

By Pete Barbrook-Johnson

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.