Integration and Implementation Insights
A global, comprehensive, living toolkit improving research, education and impact on complex real-world problems
By Gerald Midgley
Why does the theory and practice of co-creation need to be informed by systems thinking? Co-creation without a thorough understanding of systems thinking can be deeply problematic. Essentially, we need a theory and practice of systemic co-creation.
Three key things happen in any co-creation:
By Suzanne A. Pierce
Ask most 21st century citizens whether they like technology and they will respond with a resounding, “Yes!” Ask them why and you’ll get answers like, “Because it’s cool and technology is fun!” or “Technology systems help us learn and understand things.” Or “Technology helps us communicate with one another, keep up with current events, or share what we are doing.” Look at the day-to-day activities of most people on the planet and you’ll find that they use some form of technology to complete almost every activity that they undertake.
When you think about it, technologies are really just tools. And we humans are tool users of old.
By Alison Singer
I don’t see the world in pictures. I mean, I see the world in all its beautiful shapes and colors and shadings, but I don’t interpret the world that way. I interpret the world through the stories I create. My interpretations of these stories are my own mental models of how I view the world. What I can do then, to share this mental model, is create a more formalized model, whether it is a simple picture (in my case a very badly drawn one), or a system dynamics model, or an agent-based model. People think of models as images, as representations, as visualizations, as simulations. As tools to represent, to simplify, to teach, and to share. And they are all these things, and we need them to function as these things, but they are also stories, and can be interpreted and shared as such.
By Nagesh Kolagani
Citizens are increasingly coming together to solve problems that affect their communities. Participatory modeling is a method that helps them to share their implicit and explicit knowledge of these problems with each other and to plan and implement mutually acceptable and sustainable solutions.
While using this method, stakeholders need to understand large amounts of information relating to these problems. Various interactive visualization tools are being developed for this purpose. One such tool is ‘serious gaming’ which combines technologies from the video game industry – mystery, appealing graphics, etc., – with a purpose other than pure entertainment, a serious, problem driven, educational purpose.
By Jen Badham
As a modeller, I often get requests from research or policy colleagues along the lines of ‘we want a model of the health system’. It’s relatively easy to recognise that ‘health system’ is too vague and needs explicit discussion about the specific issue to be modelled. It is much less obvious that the term ‘model’ also needs to be refined. In practice, different modelling methods are more or less appropriate for different questions. So how is the modelling method chosen?
Sometimes the colleague will actually name a technique, for example ‘we want an agent-based model of an intervention to encourage physical activity’. However, this choice may not be informed. It might reflect something that he or she saw in a paper, at a conference, or whatever some previous modeller used. On the other hand, the colleague may have sufficient knowledge to have consciously selected an appropriate method.
From the other direction, many modellers work with only system dynamics or agent-based modelling or some other specific technique.
By Deana Pennington
Over a decade ago I became interested in the role of external artifacts in enabling knowledge synthesis across disciplinary perspectives, where external artifacts are any simplified physical representation of real phenomena that enable human manipulation of complex concepts. A simulation model is one example of an external artifact. In general every simplified representation of reality is a model, whether that representation occurs in our heads (mental models), on paper (conceptual models) or in a sophisticated computer-based simulation model. And so I embarked on a research agenda to understand the role of data, models, and other forms of external representations in enabling integration and synthesis across perspectives.
By Klaus Hubacek and Christina Prell
Being responsive to stakeholder interests and suggestions is important for successful participatory modeling. We share lessons from an exciting, five year project in the UK entitled the ‘Sustainable Uplands’. The project sought to bring together a variety of groups ranging from academics, policy makers, residents, conservationists, and different ‘end user’ groups that all, in some way, held a stake in upland park areas in the UK.
Our process was iterative, tacking back and forth between field work, consultations among the research team, consultations with non-academic stakeholders, and modeling. Not only were our models heavily influenced by what stakeholders told us were important values and considerations regarding upland areas, but these also informed how we went about gathering the data.
By Laura Schmitt Olabisi
Who can make systems change? The challenges of complexity are intensely felt by those who are trying to make strategic interventions in coupled human-environmental systems in order to fulfill personal, societal, or institutional goals. The activists, leaders, and decision-makers I work with often feel overwhelmed by trying to deal with multiple problems at once, with limited time, resources, and attention. We need tools to help leaders cut through the complexity so that they can identify the most effective strategies to make change.
This is where participatory system dynamics modelers like myself come in.
By Patricia Gober
Efforts to improve the use of models to support policy and practice on water resources issues have increased awareness of the role of advocacy and public engagement in the modeling process. Hydrologists have much to learn from the recent experience of climate scientists who have discovered that scientific knowledge is not independent of the political context in which it is used but rather is co-produced by scientists and society.
Despite a strong consensus among climate scientists in the Intergovernmental Panel on Climate Change’s (IPCC) 2013 report that “warming of the climate system is unequivocal,” approximately one-third of the USA’s population still does not believe that global temperatures have risen over the past 100 years and does not trust the things that scientists say about the environment.
An English version of this post is available
La modélisation participative cherche à impliquer un groupe de personnes dans la conception et la révision d’un modèle. L’objectif à terme consiste à mieux caractériser les problèmes actuels et imaginer collectivement comment tenter de les résoudre. Dans le domaine de l’environnement en particulier, il apparaît nécessaire que les acteurs concernés se sentent impliqués dans la démarche de modélisation, afin qu’ils puissent exprimer leurs propres points de vue, mais aussi pour mieux s’engager dans des décisions collectives. De ce fait, pour aborder la gestion intégrée des ressources, il est nécessaire de mettre les acteurs au centre des préoccupations de recherche, à la fois lors de la phase la conception du modèle mais aussi pour l’exploration de ces scénarios.
By Miles McNall
What are the results of participatory modeling efforts? What contextual factors, resources and processes contribute to these results? Answering such questions requires the systematic and ongoing evaluation of processes, outputs and outcomes. At present participatory modeling lacks a framework to guide such evaluation efforts. In this post I offer some initial thoughts on the features of this framework.
A first step in developing an evaluation framework for participatory modeling is to establish criteria for processes, outputs, and outcomes. Such criteria would answer a basic question about what it means when we say that a participatory modeling process, output, or outcome is good, worthy, or meritorious.
By Pete Loucks
When computer technology became available for developing and using graphics interfaces for interactive decision support systems, some of us got excited about the potential of directly involving stakeholders in the modeling and analyses of various water resource systems. Many of us believed that generating pictures that could show the impact of various design and management decisions or assumptions any user might want to make would give them a better understanding of the system being modeled and how they might improve its performance.
We even got fancy with respect performing sensitivity analyses and displaying uncertainty. Our displays were clear, understandable, and colorful. Sometimes we witnessed users even believing what they were seeing. We occasionally had to remind users that our models were, and would continue to be, approximations of reality, at best. It was fun developing and using such tools, and indeed today most models that are used to analyze river basins, groundwater, and coastal zones incorporate interactive, graphics-based, decision support frameworks.