Iteration and Innovation: Using the Right Models for Improving the Use of Research in Policy and Practice

studentsubmission2014thumbThis post briefly describes several models for research-policy and research-practice relationships, and then explores how two models– the interactive model and the context, evidence, and links model– best capture the complexities inherent in the use of climate change research in policy and practice. This post argues that models that promote the understanding of context, the fostering of networks, and the promotion of risky and innovative thinking provide a more complete guide for improving the use of research in policy and practice.

Research-policy models

The traditional or rational model has a linear, cyclical structure that progresses through four clear stages: “problem identification and agenda setting, decision making, policy implementation, monitoring and evaluation” (Nutley, Walter, & Davies, 2007, p. 93). Under this model, policy makers use research in a neat, linear fashion to reach a decision (Nutley et al., 2007). Rational models have research at the heart of policy making and place expectations on extensive consultation. They fail to reflect the complexity of the policy-making process or the intricate interactions that occur between the research and policy communities (Nutley et al., 2007). These models tend to focus on the instrumental use of research and neglect other potential uses of research in policy-making (Nutley et al., 2007).

Unlike the rational models, the two-communities model identifies a fundamental gap between research and policy. This gap occurs due to cultural differences between the humanities and the sciences (Nutley et al., 2007). The model argues that researchers and policy-makers live in two separate worlds with different and conflicting values, reward systems, and languages (Nutley et al., 2007). The disconnect between the two groups means policy-makers will not adequately use research from the science community.

The policy network model provides a more complete understanding of how research and policy connect. It includes other parties like interest groups, policy communities, advocacy coalitions, and epistemic communities (Nutley et al., 2007). Policy networks expand the range of participants in the research-policy interface beyond simply researchers and policy makers (Nutley et al., 2007). The context, evidence, and links model further builds on the policy network model through including a discussion of how context, evidence, and links shape the use of research in policy making. This model argues that research use is a dynamic, complex and mediated process (Nutley et al., 2007). Formal and informal structures, multiple actors and bodies of knowledge, and the relationships and play of politics all work together in a complex fashion to shape the process (Nutley et al., 2007).

Research-practice models

The models for research-practice follow a pattern similar to the models for research-policy. Like rational research-policy models, traditional models for the research-practice interface are linear and simplistic. These models see research and practice as “distinct and separate: knowledge is produced by researchers, then transferred through dissemination processes to practitioners who apply it” (Nutley et al., 2007, p.111).

The context-focused model improves on the traditional viewpoints through recognition that the use of research is largely dependent on context. This view argues that researchers recognize that the “real meaning of research is contingent” (Nutley et al., 2007, p. 116). It emphasizes the dynamism and interconnectedness inherent in research use relationships. The interactive model takes this role of context and expands its significance to argue that the shared views of researchers and research users can be complex, oppositional, and multi-dimensional (Nutley et al., 2007). Interactive models provide a more complete framework for understanding the integrative complexities of the research-practice relationship (Nutley et al., 2007). The interactive model helps to supplement the context, evidence, and links model through emphasizing research use as a “messy and dynamic set of interactions” (Nutley et al., 2007, p. 118).

Analysis

Traditional or linear models for research-policy and research-practice cannot adequately capture the complex nature of interactions between research and policy-makers and practitioners. The integrated context, evidence, and links model offer the best way to understand how research is used in policy and practice. Framing the discussion of climate change issues through this model argues for research communities to move away from a perspective that assumes an instrumental, linear, and static use of research. It stresses the need to encourage conceptual use of research and promote continual interaction, iteration, and networking between users and producers of information.

Focusing on the role of context in influencing the use of research is a fundamental tenet of the context, evidence, and links model. This viewpoint argues that “political and institutional structures” and the power relationship amongst these structures often influence the way research is used during policy-making (Nutley et al., 2007). Dilling and Lemos (2011) identify a list of contextual factors that impact the use of climate change research. These authors argue that institutional or organizational settings often shape the usability of seasonal climate forecasting (SCF) for policy decisions. An organization with inflexible rules will often respond to the information in a different way than an organization that is more flexible with its policies. Similarly, if an organization generally favours established, traditional, and tested practises, then it will often treat unproven innovations in a more skeptical manner than an organization with a more innovative culture. Reward structures also play a substantial role in deciding how much information will influence policy in climate change issues. If a particular political system rewards short-term gains, then the decision makers in that system will be resistant to forecasts that promote long-term benefits (Dilling & Lemos, 2011). All these factors contribute to the organizational context that impacts the use of climate change research in decision making.

The importance of context in shaping the use of research in policy and practice means the producers of information need to adapt their evidence to fit the situation. The context, evidence, and links model argues that policy makers actively engage with research through filtering evidence through pre-existing knowledge, values, and experiences (Nutley et al., 2007). Dilling and Lemos (2011) support this argument by claiming that climate change researchers need to adapt their presentation and evaluation of SCFs depending on the community they serve. An adaptable (or even risky) approach will often better match the variable and contextual nature of climate change policy (Dilling & Lemos, 2011). This need for adaptation means that researchers will often need to meditate, translate, and co-produce the research with decision makers (Nutley et al., 2007). The context, evidence, and links model helps to establish that climate change research is not static or linear. Evidence (e.g., SCFs) is a separate entity, which is subject to adaptable and contextual forces.

This contextual nature of SCFs and the dynamic process of climate change research necessitate the continual interaction between different users and producers of this research. Dilling and Lemos (2011) stress that iteration and collaboration between the users and the producers of climate change research greatly improve the knowledge and adoption of SCFs in a community. This process of “sustained interactivity” allows producers of information to gain valuable inside knowledge about the use of their research, which they can then use to better customize the presentation of the information (Nutley et al., 2007, p. 117). The interactive context, evidence, and links model also helps to explain the importance of establishing networks in climate change research. Dilling and Lemos (2011) argue that information brokers create the links between producers and users of climate change information. These boundary groups connect disparate interests and organizations to create expanded “chains of legitimacy,” which increase the use of research in policy decisions (Nutley et al., 2007, p. 111). With a problem as complex as climate change, continual and sustained communication between the producers and users of knowledge is essential. Linear, static, or divided models do not capture the significance of this type communication in promoting the use and influence of research.

Morton, Rabinovich, Marshall, and Bretschneider’s (2011) paper about framing climate change research further supports the argument that the impact of research on practice and policy depends heavily on contextual, adaptable, and interactive factors. The authors argue that because of the high uncertainty of research surrounding climate change, framing research has a direct impact on its effectiveness in convincing people to take action. Their study found that when climate change predictions were communicated in terms of gains (positive framing), uncertainty produced significantly stronger intentions to act than when communicated in terms of loses (negative framing) (Morton et al., 2011). In sum, “when communicating the uncertainties of climate change, a positive frame was more effective at stimulating action than a negative frame” (Morton et al., 2011, p.107). While the study focused on the perceptions of the general public, it lends insight into how the communication of research depends heavily on framing or fitting research to specific contexts and purposes. The influence of research on practice and policy is often context-dependent, so the communication of research needs to be dynamic, malleable, and fit-to-purpose. Research is not a singular, objective, static thing passed passively from one group to another. The meaning and significance of research change based on a wide range of social, cultural, and political factors.

Conclusion

The significance of organizational factors, adaptability of research, interactivity, and framing in the use of climate change research illustrates the need for a model that can adequately capture these factors in the research-policy and research-practice interfaces. The interactive and context, evidence, and links models offer the best paradigm for navigating this complex subject because it shifts the assessment of the use and influence of research from instrumental to conceptual (the fostering, encouraging, and assessing of links, connections, and relationships). The complex, interdependent, and messy nature of environmental issues means that this model for research use has application beyond climate change issues. Scientific research in general must integrate itself in organizational and cultural contexts, foster and maintain networks, and promote risky and innovative thinking.

 

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.

Morton, T. A., Rabinovich, A., Marshall, D., & Bretschneider, P. (2011). The future that may (or may not) come: How framing changes responses to uncertainty in climate change communications. Global Environmental Change, 21(1), 103-109.

Nutley, S. M., Walter, I., & Davies, H.T.O. (2007). Using evidence: How research can inform public services. Bristol: The Policy Press.

Authors: Ijay Nnabuo, Andrew Roy, and Amani Saini

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.