Effective communication is a popular phrase within many institutions. At a basic level, communication involves purposeful exchange of information among parties. Failure to successfully transfer knowledge within this transaction can result in misunderstanding, misuse of time, and inappropriate or lack of action. Within a governmental context, this situation could result in wasted resources, ineffective policy, and a poor reflection of the importance of public or environmental welfare. Evidence-based decision-making depends on meaningful communication between research knowledge producers and research users, in this case, decision makers. Research (natural and social science) can be the foundation for many decision-making processes. The conceptual framework for the communication of scientific research to decision-making settings is academically referred to as the science-policy interface (SPI), 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)
Effective, dynamic transfer of knowledge between the research and policy communities can promote the development of robust, comprehensive policies, based on the best available evidence. To navigate SPIs for optimal communication, the identification of enablers and barriers to information exchange will aid in bridging the gap between the two areas. Through discussion of learning style frameworks for effective communication, this blog post briefly outlines enablers and barriers to research information communication, the institutional dynamics of research communication and use, and the social component of communication illustrated by an example, namely, resilience science and SPIs.
Communication and Learning Styles
As communication is the flow of information coupled with the goal of understanding the transferred information, the receiver is expected to gain knowledge in the exchange. Decision-makers do learn from scientists as a result of the communication activities of SPIs. Optimally, the goal of the exchange is the application of the research in policy. Nutley, Walter, and Davies (2012) define communication of information as an active process during which the concepts and research findings are given meaning in a policy context through collaborative translation and adaptation by researchers and policy makers. To foster meaningful information exchange, communication of research within SPIs could be guided by learning style frameworks. For example, the organizational learning style of generative learning, where knowledge is acquired in an adaptive process that engages self-regulating behavior to guide the learning process (2012), could be used to guide the movement of research into policy. Osborne and Wittrock (1983, p. 493) point out that “in order to learn with understanding, a learner has to construct meaning actively.” Generative learning allows participants to engage in an active learning process with feedback loops for the evaluation of knowledge transfer based on the standards of communication within the learning framework. To achieve generative learning, organizations can promote learning through the following: encouraging individuals to develop their capacity to engage with others, fostering team learning which is naturally a collaborative learning style, addressing individuals’ mental modes to avoid inappropriate application of personal assumptions and generalizations, and allowing for open system thinking to achieve integrated big picture learning (Nutley et al., 2012). Organizational learning can enrich understanding of how research can be applicable to policy, because generative learning fosters collaborative and flexible progression of knowledge uptake which ultimately connects social learning to the conceptual perspective of communication in SPIs (Arts et al., 2016). The guiding principles of generative learning can be adopted by an institution to encourage effective communication. Despite the benefits of this learning style framework, communication and learning can easily be derailed if the guidelines are not followed appropriately, resulting in redefinition of the goals, norms, policies and procedures of the learning process (Nutley et al., 2012). To safeguard against misguided application of the framework, institutions should define the standards of the learning process in order to manage the guidelines, ensure financial and human resources are available, and define institutional priorities to meet the communication objectives (Arts et al., 2016). A balance of institutional dynamics between structured and adaptive organizational application of the learning framework will safeguard against miscommunication of research for policy development.
Communication Tools and Methods
To guide the communication of research into policy, the institutional frameworks to support the mechanisms of research use and the communication tools should be analyzed to identify the enablers and barriers. Nutley et al. (2012) name five communication factors for effective research use: dissemination, interaction, social influence, facilitation, and incentives and reinforcement.
Organizations producing research-based information should review the methods for disseminating research to policy makers, since in order for information to be useful, policy makers must understand the information they receive. Consideration of the audience, i.e., the policy makers, in terms of preferred methods for acquiring information, access to research information, and knowledge translation in the form of language and terminology, are key features of effective dissemination strategies (Cossarini et al., 2014). For example, decision-makers often use grey literature to gain an understanding of research, instead of directly consulting technical scientific journal articles. Optimal production of grey literature will tailor the publications to the information needs of audiences, which means using appropriate language, promoting materials to audiences, often via multiple methods, and utilizing publication guidelines to ensure the information will be useful to particular audiences (2014). Today, a variety of information and communication technologies (ICTs) can be used as dissemination tools. The most obvious is a website that promotes use of research through digital publication and distribution. The misperception that ICTs are by themselves a solution to communication difficulties, without attention to adequate communication of the research may actually be a dissemination barrier (2014). Generally, organizations should embrace the use of new technologies as communication media and remain adaptable to digital innovation.
Interactions between the research, policy, and practice communities foster collaborative partnerships. These relationships form when there is a balance of respect for all disciplines (Nutley et al., 2012). The integrative approach for the use of research in policy development can be strengthened when scientists are more actively involved in decision-making processes, and they are recognized as valuable stakeholders. An institution’s organizational framework that actively engages stakeholders will be beneficial for the meaningful communication of information (Arts et al., 2016). Establishment of feedback mechanisms within the institutional framework will enable effective collaboration among stakeholders instead of false institutional objectives.
Social influence can also be used advantageously for research communication. Influential individuals can persuade others of the value of the collaboration (Nutley et al., 2012). The reputation of particular scientists can increase the credibility of research, thereby increasing the communication and potential use of research. Social influence can be extended further through framing theory.
Framing theory recognizes that the words chosen to convey a given issue can exert a powerful effect on how audiences process and perceive messages by bringing certain considerations to mind over others. (McComas, Schuldt, Burge, & Roh 2015, p. 45)
The use of research in policy could be amplified through the strategic selection of language and coupling of issues. For example, combining public health concerns with climate change problems increased public acceptance of a policy due to higher social concern for public health over climate change (McComas et al., 2015).
Nutley et al. (2012) also note that the transfer of research knowledge to application in policy or practice can be facilitated by financial and human capacity resources. If institutional frameworks provide human and financial support for communication, the capacity for research communication will be enhanced.
Finally, incentives with positive and negative consequences can be used as a strategy to enable more effective research communication and use. Incentives in the form of career advancement opportunities or financial compensation could be implemented to strengthen the communication and use of research. Evaluation of various actors regarding research communication and use could result in either positive of negative outcomes (2012). Publication incentives, such as customizing publications for research use, could be implemented to overcome scientists only placing attention on publication and not research use. Additionally, incentives could be extended to managers or research producing organizations to encourage effective research communication. Creation of useable research publications could increase accountability for research investments, meaning that to receive a return on investment, research would be designed to solve real problems (Milkoreit, Moore, Schoon, & Meek. 2015). This latter approach could positively be enforced through grants to continue research initiatives or through other means of support.
Due to the complex communication interactions within SPIs, a hybrid discipline that mediates science and policy could help. For example, resilience science is one approach to institutional change through the communication of social-ecological systems (SES) functioning in governance and policy processes (Milkoreit et al., 2015). Resilience science can bridge the gap between science and policy by its adaptive framework, openness to learning from change, its fostering of participatory processes to highlight collective action to solve social problems across scales, and its promotion of polycentric governance, a collaborative multi-level governance structure (2015). This discipline utilizes a diversity of engagement techniques to create links from science to policy. However, resilience scientists can be labelled as environmentalists, thereby raising questions about the credibility of the research (2015). Unfortunately, environmental advocacy is demeaned in some scientific circles on the assumption it is generally less credible due the alleged absence of objective scientific methodology. Since environmental problems as also often social problems, a discipline like resilience science can help to address these complex issues effectively. Environmental issues are often human behavior management problems, which means they are social and political issues, not exclusively the domain of environmental management. The integration of societal values within scientific work entails ethical and moral concerns. Modernism has fostered rationality as a guiding principle in contrast and often opposition to morality, emphasizing objective efficiency and possibly rejecting the human component (Atsuji, Ueda, & Fujimoto 2014). A discipline like resilience science that integrates science with the complex social aspects of society may be helpful in effectively communicating science to policy.
Conclusion
The communication of science to policy contexts is foundational to evidence-based decision-making. However, communication between scientists and policy makers in SPIs is non-linear and should be structured to effectively incorporate all relevant actors within a meaningful exchange of information for optimal policy development processes. A structured framework that includes an evaluation process to ensure communication and use of research can be an important enabler. If such a structure is not adequately established, however, a barrier to communication is likely to occur. Viewing the communication of research information as a learning exercise, can enable information use as research will be understood and applied in practice and policy implementation. Overlooking the fact that information flow within SPIs is a social process can result in a major barrier to information use. Bridging science and policy communities requires understanding of the human or social component, and should not be thought of as unimportant. A hybrid discipline to facilitate information exchange or acceptance of the social component could be the greatest enabler to research information communication for policy processes.
References
Arts, K., Ioris, A. A. R., Macleod, C. J. A., Han, X., Sripada, S. G., Braga, J. R. Z., & Van der Wal, R. (2016). Environmental communication in the Information Age: Institutional barriers and opportunities in the provision of river data to the general public. Environmental Science & Policy, 55, 47–53. http://doi.org/10.1016/j.envsci.2015.08.011
Atsuji, S., Ueda, K., & Fujimoto, R. (2014). Our stolen sustainability: Unsafe Eden contaminated by environmental hormones. Economic & Political Studies Series, 135, 1–18.
Cossarini, D. M., MacDonald, B. H., & Wells, P. G. (2014). Communicating marine environmental information to decision makers: Enablers and barriers to use of publications (grey literature) of the Gulf of Maine Council on the Marine Environment. Ocean & Coastal Management, 96, 163–172. http://doi.org/10.1016/j.ocecoaman.2014.05.015
McComas, K. A., Schuldt, J. P., Burge, C. A., & Roh, S. (2015). Communicating about marine disease: The effects of message frames on policy support. Marine Policy, 57, 45–52. http://doi.org/10.1016/j.marpol.2015.02.012
Milkoreit, M., Moore, M. L., Schoon, M., & Meek, C. L. (2014). Resilience scientists as change-makers—Growing the middle ground between science and advocacy? Environmental Science & Policy, 53, 87–95. http://doi.org/10.1016/j.envsci.2014.08.003
Nutley, S. M., Walter, I., & Davies, H. T. O. (2007). Using evidence: How research can inform public services. Bristol, UK: Policy Press.
Osborne, R. J., & Wittrock, M. C. (1983). Learning science: A generative process. Science Education, 67(4), 489–508. http://doi.org/10.1002/sce.3730670406
Author: Kendra Moore
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.
