The International Institute for Applied Systems Analysis (IIASA), the Centre for Systems Solutions (CRS) and the University of Ottawa’s Institute for Science, Society and Policy (ISSP) are collaborating to deliver a policy simulation exercise at this year’s Canadian Science Policy Conference. Drawing on the CRS’ Cascading Climate Risks Simulation developed for the European context, this simulation focuses on the future of Arctic trade and governance in light of the impacts of climate change. Our aim is three-fold: to foster awareness and understanding of this important issue for Canada and other Arctic nations, to assess the effectiveness of policy simulations as both a training and policy development tool, and to engage CSPC attendees in a novel means of exploring the relationships between science, society and policy. 

What is a policy simulation? Why are simulations an important toolkit for science policymakers? How will our simulation work? We address these questions below, and hope CSPC attendees will join us in this exciting endeavour.

Policy simulations help to bring researchers, policymakers and society together with the aim of collectively addressing complex problems. Multiple gaps exist between science and “science users” – including policy makers. As a result, existing knowledge is not applied as effectively as it could be to real world circumstances. Many have noted that researchers are often more engaged with the process and results of their research, than they are with how end users will use this information. Research is often presented in peer-review publications, often written using complex terminology that is only accessible to experts in the field in ways that are not immediately obvious to the policy making community.  On the opposite side, decision-makers do not always use the most appropriate available scientific information to make policy decisions, often due to time pressures, but also due to accessibility issues. The importance of addressing such gaps, and the value of facilitating evidence-informed decision making practice is well documented, having been specifically highlighted within the Sendai Framework, and in the broader research community.

At the same time, problems are increasing in complexity, catalyzed by current circumstances including the ongoing global pandemic, the developing climate emergency and rapidly changing economic, social, and environmental landscape – many of which are interconnected. This perceived complexity can be seen from two perspectives: technical and problem-oriented (complexity as a result of interactions between the “hard” biophysical, technological, or economic components of a system), and people-oriented (complexity as a result of the strategic interactions among the main actors on the political scene). Both the multitude of real-life problems and the tensions arising from the diverse ways people approach them combine to create a highly uncertain and ambiguous environment that impedes collective planning for emerging challenges.

Policy simulations aim to bridge the gap between science and science users, and to create an environment for navigating complexity in a meaningful way. They offer a promising tool for addressing complexity-related challenges because they integrate both problem-oriented (technical, physical, economic) and people-oriented (relational, social, psychological, ethical) complexities. In these circumstances, complex problems are recreated as simplified models of real complex systems, through agreed upon procedures and practices. In this way, simulation designers can procedurally represent the key aspects of complex real-world problems. Participants can then actively operate the simulated environment to experience these processes in action. The multi-actor aspect of complexity is taken into account, as participants adopt roles and interact with many people of different backgrounds and values. In this way, participants learn not only how to set collective goals and collaborate to achieve them, but also how to empathize with others, understand their perspectives, and negotiate consensus. 

Policy simulations foster collaboration between stakeholders and scientists by providing opportunities to analyze how problems emerge in complex systems and where points of intervention and contention may lie. Policy simulation activities create room for instant feedback and self-reflection, they challenge mental models on which decisions are based, and they allow for double-loop learning, leading to better understanding and future planning. Flexibility is an important feature of simulations, allowing the integration of a variety of methods – literally “anything useful” – from the area in which it is applied.

The Cascading Climate Impacts Simulation is a narrative-oriented experience that brings the participants to the near future (sometime between 2027 and 2035). Participants assume roles of representatives of various countries and organizations responsible for global safety and well-being. In these roles, they discuss and react to current affairs on an online platform. They are confronted with a scenario of dramatic events caused by the climate crisis, that starts from a global agricultural crisis leading to trade and supply chain disruptions. The participants are invited to working groups where they are asked to give their advice regarding some propositions for counteracting the emerging crises.

The original concept for this simulation was developed and implemented for the first time as part of the CASCADES project, funded by the Horizon 2020 EU program. The project aims to identify how the risks of climate change faced by countries, economies, and peoples from outside Europe might cascade into Europe. The latest version of the Cascading Climate Risks simulation – the Arctic Future Simulation – focuses on the Arctic – a geographic region very relevant to Canada – and the consequences of climate change for the region’s politics. With new threats and opportunities arising, and pressure coming from political actors all around the globe, the representatives of concerned countries and organizations (scenario participants) will deliberate on possible directions for future Arctic policies. Their discussions and negotiations are informed by the input from the (fictitious) Arctic Science Network that actively participates in the process. Together, all the actors work towards crafting an Arctic treaty that will shape the future of the Polar region.

With this policy simulation, the International Institute for Applied Systems Analysis), the Centre for Systems Solutions and the Ottawa’s Institute for Science, Society and Policy are collaborating to deliver an engaging, immersive and context relevant exercise at CSPC 2020. IIASA’s policy-oriented systems analysis research focuses on issues too large or complex to be solved by a single country or academic discipline. CRS enhances knowledge brokering, science-policy integration and social dialogue through innovative methods and system tools, such as policy simulations. The ISSP’s interdisciplinary research cuts across science policy, policy for science and governance of emerging technologies, and provides an ideal backbone of Canadian context and expertise for a Canadian science policy audience. A simulation based on climate cascades in the Arctic sits at the confluence of our mandates – and provides a unique and valuable training, development and awareness-raising activity. 

Policy simulations are a powerful tool for thinking through complex problems with no easy answers. It forces participants to take the perspectives of various stakeholders into consideration, while having to make difficult decisions that weigh trade-offs between different inputs and consider possible collateral consequences. Governance in a rapidly changing Arctic is a permanent challenge for Canada, Indigenous Peoples, allies and adversaries alike. With this simulation, we hope to facilitate a dialogue, helping build an understanding of the gaps between researchers and research users, and how best to bridge them towards developing effective evidence-informed policy.  We hope you will join us in this innovative session at this year’s CSPC and look forward to seeing you there!

References

The Cascading Climate Impacts was developed within the CASCADES: Cascading Climate Risks Towards Adaptive and Resilient European Societies, funded by European Union’s Horizon 2020 research and innovation programme under grant agreement No 821010.

• Aitsi-Selmi, A., Murray, V., Wannous, C., Dickinson, C., Johnston, D., Kawasaki, A., … & Yeung, T. (2016). Reflections on a science and technology agenda for 21st century disaster risk reduction. International Journal of Disaster Risk Science, 7(1), 1-29.
• Argyris, C. (1991). Teaching Smart People How to Learn. Harvard Business Review. Distributed by The New York Times Special Features/Syndication Sales.
• Bogost, I. (2008). The Rhetoric of Video Games. Cambridge, MA: The MIT Press.
• Duke, R. (1980). A paradigm for game design. Simulation & Gaming 11(3), 364-377.
• Gaillard, J. C., & Mercer, J. (2013). From knowledge to action: Bridging gaps in disaster risk reduction. Progress in human geography, 37(1), 93-114.
• Geurts, J. L. A. Duke, R. D. and Vermeulen, P. A. M. (2007). Policy Gaming for Strategy and Change. Long Range Planning 40 (2007), 535–558.
• Harvey, S., Liddell, A., & Mcmahon, L. (2009). Windmill 2009. King’s Fund.
• Ladousse, G.  P. (1987) Role Play. Oxford University Press.
• Mayer, I.S. (2009). The Gaming of Policy and the Politics of Gaming: A Review. Simulation & Gaming 40(6), 825–862.
• Mochizuki, J., Magnuszewski, P. and Linnerooth-Bayer, J. (2018). Games for Aiding Stakeholder Deliberation on Nexus Policy Issues.In: Managing Water, Soil and Waste Resources to Achieve Sustainable Development Goals. Eds. Hulsmann, S. & Ardakanian, R., 93-124. DOI:10.1007/978-3-319-75163-4_5.
• Reyers, B., Nel, J. L., O’Farrell, P. J., Sitas, N., & Nel, D. C. (2015). Navigating complexity through knowledge coproduction: Mainstreaming ecosystem services into disaster risk reduction. Proceedings of the National Academy of Sciences, 112(24), 7362-7368.
• Taylor, J. (1971). Instructional planning systems: A gaming-simulation approach to urban problems. Cambridge, UK: Cambridge University Press.
• Toth, F.L. (1988) Policy Exercises: Objectives and Design Elements. Simulation & Games, 19(3), pp. 235-255
• UNISDR (2015). Sendai Framework for Disaster Risk Reduction 2015 – 2030.
• Vogel, C., Moser, S. C., Kasperson, R. E., & Dabelko, G. D. (2012). Linking vulnerability, adaptation and resilience science to practice: Pathways, players and partnerships. In Integrating Science and Policy (pp. 117-148). Routledge.
• Weichselgartner, J., & Pigeon, P. (2015). The role of knowledge in disaster risk reduction. International Journal of Disaster Risk Science, 6(2), 107-116.