An Introduction to the Science-Policy Interface Concept: What, Why, and How

Today, policy-making is often complex; policy-makers must contend with many different stakeholders and their often-conflicting interests. The rise of evidence-based policy-making over the past quarter century has further complicated policy-making, because policy makers must be aware of and are pressured to use the vast array of scientific and other research information available for informing policy. Further, researchers must learn to navigate the policy-making system in order to promote the application of their research in policy development. This relatively new reality has led to the creation of the concept of the science-policy interface. In this blog post, we briefly discuss three questions related to this concept: What is the science-policy interface? Why do such interfaces exist? How does and how should the science-policy interface operate?

What is the Science-Policy Interface?

The science-policy interface has been defined as “social processes which encompass relations between scientists and other actors in the policy process, and which allow for exchanges, co-evolution, and joint construction of knowledge with the aim of enriching decision-making” (van den Hove, 2007, p. 807). Key to this definition is the variety of actors involved in the interfaces. Gluckman argues that within the science-policy interface there are four categories of roles: knowledge generators, knowledge synthesizers, scientists who aggregate and try to understand the knowledge, and knowledge brokers (Gluckman, 2018). These categories include significant actors such as the researchers, policy makers, and boundary organizations that attempt to connect and mediate between science and policy. However, more important to this definition, perhaps, is the reference to exchanges of information and interactions for the co-evolution and joint construction of knowledge between scientists and the other actors. Many actors within the science-policy interface, including scientists, policy makers, and journalists, have noted a gap between science and policy, including the availability of science that is directly applicable for policy-makers to use and its actual take up in policy (MacDonald, Soomai, De Santo, & Wells, 2016). The science-policy interface, when optimally employed, helps to close this gap, creating an environment where scientific research can easily be shared with policy makers who can use it to inform decision-making.

Why does the Science-Policy Interface Exist?

The nature of science creates many opportunities for intersection with policy, particularly in the case of issue-driven science: when science and policy focus on solving the same issue, scientists and policy-makers will give attention to similar priorities, disciplines, and methods, which potentially trigger an effective science-policy interface. Good policy requires both facts, derived from scientific analysis, and values derived from policy analysis (Saner, 2007). However, simply providing more scientific information does not mean better policy (Sutherland, Spiegelhalter, & Burgman, 2013). The science-policy interface helps to negotiate and mediate between science and policy. Through the numerous processes within the interface, scientists are able to inform policy better by providing evidence to policy-makers as well as other stakeholders. The science-policy interface helps to close the gap between scientific interests and policy priorities. Scientists will learn about policy makers’ requirements and policy makers will build understanding of scientists’ capacity (Dunn, Bos, & Brown, 2018).

Scientists and policy-makers often have different motivations and values related to their involvement in the science-policy interface. Scientists may require more incentives to be engaged in the science-policy interface processes as they tend to be motivated and focused primarily on producing research publications. In contrast, policy-makers typically are concerned with quickly moving from one topic to another within policy agendas to avoid focusing only on narrow policy issues (Sarkki et al., 2014). The values of the two groups can also conflict since scientists are usually interested in thorough research that is public and transparent, whereas policy-makers require information for decision-making within short time frames (Sarkki et al., 2014). Creating science-policy interfaces helps scientists and policy-makers to find common ground to help with policy development.

How Does and How Should the Science-Policy Interface Operate?

Dunn et al., (2018) reviewed literature on the intersections among scientists and policy actors, conceptualizing three main models of the science-policy interface: science-push, policy-pull, and co-production (Dilling & Lemos, 2011). The science-push model tends to emphasize the pursuit of pure knowledge rather than knowledge applicability. Therefore, this model is generally ineffective at informing policy-making especially for complex socio-ecological problems such as climate change (Dunn et al., 2018), because the knowledge generated can be difficult to understand and may lack obvious applicability through a policy lens. In the policy-pull model, science is used to provide solutions or supportive evidence for a policy. However, sometimes it is not feasible for science to provide such solutions due to limited data and capacity of researchers. Science and policy co-production is a model that can balance the limitations of the other two models. Effective co-production is a true partnership between scientists and policy makers. The co-production process is on-going, usually highly interactive, and flexible, requiring mutual trust, respect, participation and commitment from both researchers and policy makers (Perry & Atherton, 2017). While much of the available literature focuses on knowledge production, in many contexts the needs of policy- and decision-makers are not well addressed. Related to the push-pull science-policy interface, a dynamic exists between supply-driven research and demand-driven research. While research on the science-policy interface shows that demand-driven research tends to be more relevant to policy development than supply-driven research, Sarkki et al. acknowledge that research that is simply supplied may be relevant for policy requirements and can create a demand for the research (Sarkki et al., 2014).

Sarkki et al. refer also to the CRELE (credibility, relevance, legitimacy) framework suggested by Cash et al. (2003), where credibility, relevance, and legitimacy are the “key determinants of the effectiveness of improving the use of science in decision-making” (Sarkki et al., 2014). Science-policy interfaces are more effective when their credibility, relevance, and legitimacy are increased. The level of each attribute can vary for each science-policy interface, based on the context of a given situation. As a result, trade-offs and synergies between the three attributes can occur and actors involved in the process may interpret the outcomes differently (Sarkki et al., 2014). Therefore, where feasible, communication between policy makers and scientists should occur frequently and early in a policy cycle. Researchers and policy-makers should communicate their values and needs to each other in order to establish mutual understanding of the policy requirements (Dunn et al., 2018).

Boundary organizations have been identified by some researchers as major actors in the science-policy interface. Jensen-Ryan and German define boundary organizations as institutions that straddle politics and science, are identified generally by the formality of their roles, and are focused on facilitating activity within the science policy interface (Jensen-Ryan & German, 2018). To expand upon this definition, boundary organizations are said to “employ specialists, known as interpreters, bridgers, or mediators, from both sides of the science-policy interface to broker links between advisors or policy-makers and scientists” (MacDonald et al., 2016, p. 33). Boundary organizations are, therefore, important for fostering communication and collaboration between researchers and policy-makers in the science-policy interface. One example of a widely recognized boundary organization is the Intergovernmental Panel on Climate Change, which has been described as “one of the most successful boundary organizations because it provides credible assessments and guidelines for policy decisions through balancing science-policy interfaces” (Gustafsson & Lidskog, 2018, p. 7).

Conclusion

In summation, science and policy often rely on each other, whether the relevant actors recognize the dependency or not. Science informs policy through evidence-based decision-making, and policy makers can inform researchers about their evidentiary needs. These inherent interrelations have created the need for science-policy interfaces, to close the gap between science and policy that often currently exists. An optimal science-policy interface is one that negotiates between the varying values of stakeholders and fosters effective communication and co-production of information between science and policy actors. Boundary organizations often take on the role of mediators within the interfaces to foster this kind of communication and co-production, and thus may be crucial for fostering a more integrated science-policy interface.

References

Dilling, L., & Lemos, M. C. (2011). Creating usable science: Opportunities and constraints for climate knowledge use and their implications for science policy. Global Environmental Change, 21(2), 680-689. https://doi.org/10.1016/j.gloenvcha.2010.11.006

Dunn, G., Bos, J. J., & Brown, R. R. (2018). Mediating the science-policy interface: Insights from the urban water sector in Melbourne, Australia. Environmental Science & Policy, 82, 143-150. https://doi.org/10.1016/j.envsci.2018.02.001

Gluckman, S. P. (2018). The role of evidence and expertise in policy-making: The politics and practice of science advice. Journal & Proceedings of the Royal Society of New South Wales, 151(part 1), 91–101. ISSN 0035-9173/18/010091-11

Gustafsson, K. M., & Lidskog, R. (2018). Boundary organizations and environmental governance: Performance, institutional design, and conceptual development. Climate Risk Management, 19, 1–11. https://doi.org/10.1016/j.crm.2017.11.001

Guston, D. H. (1999). Stabilizing the boundary between US politics and science: The role of the Office of Technology Transfer as a boundary organization. Social Studies of Science, 29(1), 87-111. https://doi.org/10.1016/j.crm.2017.11.001

Jensen-Ryan, D. K., & German, L. A. (2018). Environmental science and policy: A meta-synthesis of case studies on boundary organizations and spanning processes. Science and Public Policy. https://doi.org/10.1093/scipol/scy032

MacDonald, B. H., Soomai, S. S., De Santo, E. M., & Wells, P. G. (2016). Understanding the science-policy interface in integrated coastal and ocean management. In B. H. MacDonald, S. S. Soomai, E. M. De Santo, & P. G. Wells (Eds.). Science, information, and policy interface for effective coastal and ocean management(pp. 19–43). Boca Raton, FL: CRC Press.

Perry, B., & Atherton, M. (2017). Beyond critique: The value of co-production in realising just cities? Local Environment, 22(sup1), 36-51.

Saner, M. (2007). A map of the interface between science & policy. Policy Brief Series. University of Ottawa. Retrieved from https://issp.uottawa.ca/sites/issp.uottawa.ca/files/issp2014-spibrief6-mapoftheinterface.pdf

Sarkki, S., Niemelä, J., Tinch, R., van den Hove, S., Watt, A., & Young, J. (2014). Balancing credibility, relevance, and legitimacy: A critical assessment of trade-offs in science-policy interfaces. Science & Public Policy, 41(2), 194-206.

Sutherland, W. J., Spiegelhalter, D., & Burgman, M. (2013). Policy: Twenty tips for interpreting scientific claims. Nature News, 503(7476), 335. Retrieved from https://www.nature.com/news/policy-twenty-tips-for-interpreting-scientific-claims-1.14183

Van den Hove, S. (2007). A rationale for science–policy interfaces. Futures, 39(7), 807-826. http://dx.doi.org/10.1016/j.futures.2006.12.004

 

Authors: Elizabeth Burton, Weishan Wang, and Randolph White

 

This blog post is part of a series of posts authored by students in the graduate course “The Role of Information in Public Policy and Decision Making” offered at Dalhousie University.