How do we know when we have good answers to research questions, especially about wicked problems?
As investigators who engage the public in both modeling and research endeavors we address two major questions: Does citizen science have a place within the participatory modeling research community? And does participatory modeling have a place in the citizen science research community?
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.
I frequently struggle to explain how participatory modeling deals with uncertainty. I found useful guidance in the management literature.
How can we resolve debates about participatory processes between proponents and skeptics? What role can participatory modelling play in improving participatory processes?
Proponents argue for the merits of participatory processes, which include learning; co-production of knowledge; development of shared understanding of a problem and shared goals; creation of trust; and local power and ownership of a problem.
What can art contribute to participatory modelling? Over the past decade, participatory visual and narrative arts have been more frequently and effectively incorporated into scenario planning and visioning workshops.
We use arts-based techniques in three ways:
incorporating arts language into the process of visioning
delineating eco-aesthetic values of the visual and aural landscape in communities
engaging art to articulate challenges and solutions within local communities.
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.
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.
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.
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.