Research-based information flows from a wide variety of sources, including dissertations, websites, peer-reviewed journals, policy briefings, or conference workshops, (Nutley, Walker & Davies, 2007). The information chain is a conceptual framework that attempts to demonstrate the transfer of this information. This framework models the various pathways information follows as it proceeds from the source to the end user. Duff defines the information chain as “the institutional and documentational structure of human communication” (Duff 1997, p. 179). Therefore, the purpose of the chain is to facilitate communication between each end of the information spectrum. Information chains are comprised of two fundamental components: an author producing the information and a user intended to use the information (Duff, 1997). Mixed with a range of players from researchers to policy makers to practitioners, the information chain is a complex web of direct and indirect pathways that move information from point A to B to shape policy and decision-making (Duff, 1997; Nutley et al., 2007).
One information pathway that is difficult to illustrate is the important role that social interaction or oral transmission plays in the dissemination and acceptance of research-based information (Nutley et al., 2007; Turner, 2009). For example, individuals frequently receive information via personal contacts, training sessions, departmental meetings, emails, and other interpersonal methods. (Nutley et al., 2007). Moreover, the flow of information is a social process enhanced by communication channels (Nutley et al., 2007). Understanding the social pathway via which research-based information is transmitted will help researchers and policy makers better utilize research-based information to influence policy and decision-making. This outcome can be achieved at an individual or organizational level with increased professional development or citizen engagement. For example, if departments promoted monthly research updates, training opportunities, or conference attendance, this practice would expand access and exposure to research-information both on an individual and collective basis (Nutley et al., 2007).
While the information chain describes how information is disseminated, there is also the issue of how this information is used. Despite the importance of social interaction in the flow of research-based information, there still exist a number of factors that can encourage or inhibit the acceptance of research use. According to Nutley et al., these factors include such issues as credibility, funding structures, relevance, personal education level, limited access, and the context in which the research is being used (Nutley et al., 2007). These factors can often interrupt or divert the flow of information and therefore affect the availability of research-based information for policy and decision-makers. “Knowledge brokers” or “boundary organizations” are an important pathway for research to enter the policy field (McNie, 2007; Nutley et al., 2007; Sarewitz & Pielke Jr., 2007). Duff notes that “intermediaries should provide added value to the information chain” (Duff, 1997, p.184). It is the identification of intermediaries that characterize the various models seeking to map the transfer of information. By identifying the intermediaries at play, such models illustrate the complexity of information flows. Furthermore, modeling the information chain can serve as a useful thought exercise that helps to frame debates on the factors contributing to effective information transfer and communication such as academic standards, the advent of electronic databases, and the role of public and private sector stakeholders in the production of information (Duff, 1997). These intermediaries between the research producer and user could help improve access, presentation, and promotion of research-information to the general public, policy analysts, and practitioners. However, this process depends on the social interaction and judgement of individuals, as well as the collective which can have a positive or negative impact on the reliability of the information flow.
Scholars such as McNie advocate packaging the information that is being produced in a way that policymakers can easily implement into policy without needing too much interpretation (McNie, 2007). As well, information that has wide applicability is more likely to be considered useful (McNie, 2007). There is also an aspect of what Gladwell refers to as the “stickiness” of a message, which concerns how certain details that are distilled (and often distorted) are often also the most memorable and, therefore, likely to further the dissemination of that message (Gladwell, 2002). In distilling and packaging information, there is a certain risk of cherry-picking, whether intentional or otherwise. People and organizations are often inclined to ignore evidence that is contrary to their established beliefs and to likewise highlight evidence that supports an existing opinion (Prewitt et al., 2012). Additionally, organizational culture may influence the degree to which policy makers are inclined to accept conclusions generated by science and academic research over their own experience and insight (Prewitt et al., 2013). Others may not know that relevant information exists or be unable to retrieve it, either for reasons of access or knowledge of how to access it (McNie, 2007; Sarewitz & Pielke Jr., 2007).
Understanding the pathways of information is important for improving the process of research-use in policy and decision-making contexts. A dichotomy can exist between the source and the user in information models, creating a tension with regard to the translation of science or research into policy. The scientific and research community, thus, has historically guarded the purity of their field and insisted that it be free from external influence. As illustrated by information flow models, the product of “pure” research is filtered through various factors or intermediaries before being utilized in policy formation. Moreover, research may be forcibly altered to a certain degree to suit the context or environment. For example, we must consider the effect of research portfolios that depend on variables external to pure science, such as research funding and public lobbying. The boundary between science and policy, therefore, must be managed to balance all these factors, as ultimately science cannot exist without a society to support it, just as society’s goals are supported by the product of science. One way to balance this tension is to maintain what Prewitt et al. call a “systems perspective.” By looking at the whole system from an elevated standpoint, the systems perspective represents an opportunity to “improve cooperative interaction in research communities and among researchers, policy makers, and public groups” (Prewitt et al., 2012, p. 61). The utility of a systems perspective is its ability to aid in the understanding the long-term consequences of policies (Prewitt et al., 2012). A truly balanced representation of pure science research and policy, however, is difficult to achieve given external factors and the tendency to cherry-pick information for certain contexts.
To improve the translation of research information to policy, the social pathway of information may provide opportunities to decrease the barriers of research use. Many scholars advocate that citizens should be involved in the process, as this has been shown to foster social trust and to improve the implementation and effectiveness of policies – in spite of cries against intrusion into the purity of science (McNie, 2007). Acknowledging that the people involved in information frameworks are not only high-level policymakers or well-educated scientists is crucial. Organizational support for research- and information-seeking citizens is vital in overcoming hurdles such as lack of understanding of the research process or obstructions to access. As research has been found to spread via personal contact, it would be beneficial to research and policy communities to build greater awareness and access to new information, trends, and issues among citizens and policymakers alike. This would encourage a greater diffusion of research information and use through the information chain. To understand how the various pathways of information affect policy and decision making, we must be aware of how various sources and users produce, obtain, and interpret information at each step of the information chain.
Duff, A. S. (1997). Some post-war models of the information chain. Journal of Librarianship and Information Science, 29, 179-187.
Gladwell, M. (2002). The tipping point: How little things can make a big difference. Boston: Little, Brown & Company.
McNie, E. (2007). Reconciling the supply of scientific information with user demands: An analysis of the problem and review of the literature. Environmental Science & Policy, 10(1), 17-38.
Nutley, S. M., Walter, I., & Davies, T. O. H. (2007). Using evidence: How research can inform public services. Bristol: The Policy Press.
Prewitt, K., Schwandt, T. A., & Straf, M. L. (Eds.). (2012). Using science as evidence in public policy. Washington, DC: The National Academies Press.
Sarewitz, D., & Pielke Jr., R. A. (2007). The neglected heart of science policy: Reconciling supply of and demand for science. Environmental Science & Policy, 10(1), 5-16.
Authors: Michelle Venturini, Michael LeBlanc, and Carlisle Kent
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.