Keys to transformation: Interactions of values, rules and knowledge

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

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.
gorddard_values-rules-knowledge
Figure adapted from original in Gordardd et al. (2016)

Viewing the decision context as an interconnected system of values, rules and knowledge can reveal limits to adaptation and suggest strategies for addressing them (Gorddard et al. 2016).

Values are the set of ethical precepts that determine the way people select actions and evaluate events.

Rules are both rules-in-use (norms, practices, habits, heuristics) and rules-in-form (regulations, laws, directives).

Knowledge is both evidence-based (scientific and technical) knowledge and experiential knowledge.

Decision context is the subset of interacting subsystems that are at play in a particular decision process. One core idea is that the decision context may exclude relevant values, knowledge or rules from being considered in decisions. Adaptation may therefore involve change in the decision context.

russell-gorddard
Russell Gorddard (biography)

matt-colloff
Matthew Colloff (biography)

russell-wise
Russell Wise (biography)

michael-dunlop
Michael Dunlop (biography)

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The path perspective on modelling projects

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

tuomas-lahtinen
Tuomas J. Lahtinen (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.

Joseph H. A. Guillaume (biography)

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.

raimo-hamalainen
Raimo P. Hämäläinen (biography)

Recently, we have come to understand the importance of human behaviour in modelling and the fact that modellers are subject to biases. Behavioural phenomena naturally affect the problem solving path. For example, the problem solving team can become anchored to one approach and only look for refinements in the model that was initially chosen. Due to confirmation bias, modelers may selectively gather and use evidence in a way that supports their initial beliefs and assumptions. The availability heuristic is at play when modellers focus on phenomena that are easily imaginable or recalled. Moreover particularly in high interest cases strategic behaviour of the project team members can impact the path of the process.

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Facilitating multidisciplinary decision making

By Bob Dick

bob-dick
Bob Dick (biography)

Imagine this scenario. You are confronted by a wicked problem, such as the obesity epidemic. You know it’s a wicked problem – many previous attempts to resolve it have failed.

Suppose that you wish to develop a plan to remedy obesity. You have identified as many relevant areas of expertise and experience as you can and approached appropriate people – researchers, health practitioners, people with political influence, and so on.

You bring them together to pool their expertise—only to find that you now have another problem. Encouraging them to work collaboratively is more difficult than you expected. They talk in jargon. Their understanding is narrow. Their commitment is to their own discipline. Some of their understanding is tacit. Some of them are argumentative. And more. What are you to do?

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Should researchers be honest brokers or advocates?

By John Callewaert

callewaert
John Callewaert (biography)

When to advocate and when to be an honest broker is a question that deserves serious attention by those working on collaborative and engaged research initiatives. In my role as the Integrated Assessment director at the University of Michigan’s Graham Sustainability Institute I facilitate a wide array of collaborative research efforts. For most of our initiatives we strive to work within an honest broker frame. Following the work of Pielke (2007), the honest broker engages in decision-making by clarifying and sometimes expanding the scope of choice to decision-makers. Our recent analysis of options for High Volume Hydraulic Fracturing in Michigan[1] (fracking) and outlining sustainability goals for our Ann Arbor campus[2] are two examples which involved teams of faculty, students, practitioners and decision-makers.

The honest broker approach was particularly important for the project on fracking given the polarized views that can sometimes be associated with this topic.

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