Science-Policy Interaction

Science-policy interaction is understood here as “the ways in which research impacts on policy and policy draws on research”

Introduction

The Coastal Wiki contains much policy relevant information. Nevertheless, policy makers often complain about a lack of policy relevant research results and scientists often complain about the ignorance of policy makers of their policy relevant research results. Bridging the gap between policy and science is an issue which has triggered intensive debates over many years. No simple recipes have emerged. This article highlights some major causes of poor science-policy interaction and is intended as a help to avoid obvious pitfalls. It is more relevant for environmental and social sciences than for fundamental research.

The Knowledge Cycle

Figure: The Knowledge Cycle: an idealistic conceptual model of Science-Policy Interaction.

The knowledge cycle depicted in the figure provides an appealing model for science-policy interaction. The simplest interpretation of the picture is: science delivers facts and figures on which policy can build and policy formulates demands for lacking knowledge. However, reality is more complex. Science can produce facts and figures for specific situations, temporally and geographically, but these situations seldom match the situations of interest for policy application. Situations of policy interest often lay in future and relate to changed boundary conditions. Results of relevance for policy are obtained by extrapolation or generalisation, relying on assumptions or models. But generally there is no unique and validated set of assumptions and models available. The science input to policy is therefore cursed with uncertainty and arbitrariness. Especially in (the frequent) cases that the underlying dynamic of the system under consideration is not fully understood, different scientists may come with different answers and it may happen that no consensus can be reached. In these cases policy makers feel that science brings more confusion than clarity. Uncertainty and arbitrariness due to a lack of basic understanding of system dynamics are major flaws of the knowledge cycle.

The climate debate on the causes and impacts of global warming is an illustration of difficult science-policy interaction related to uncertainty and arbitrariness. The assessment process established by the Intergovernmental Panel on Climate Change is a good example of how to deal with this problem.

Ten Ways of Conceiving the Research Policy Dynamic

Policy makers and scientists approach problems from viewpoints that are basically different. However, better understanding these different viewpoints contributes to filling the science-policy gap. An excellent review paper Bridging Research and Policy has been written by Diane Stone, Simon Maxwell and Michael Keating, as a contribution to an international workshop held at Warwick University in 2001, funded by the UK Department for International Development. A key to understanding research policy dynamic is provided by the following ten views of the problem of science-policy interaction, which are reproduced from the review paper.

1. The problem can be defined as a public goods problem, where there is an inadequate supply of policy relevant research.

2. The problem can be defined as one of a lack of access to research, data and analysis for both researchers and policy makers. Recommendations to improve both access to and the diffusion of knowledge follow.

3. The problem can be defined as the poor policy comprehension of researchers towards both the policy process and how research might be relevant to this process. Overcoming this lack of understanding requires researchers to study the policy process, to demonstrate the relevance of research, and to build methodologies for evaluating research relevance.

4. The problem can be represented as ineffective communication by researchers their work. Improved communications strategies are consequently encouraged.

5. The problem can be defined as societal disconnection of both researchers and decision-makers from those who the research is about or intended for, to the extent that effective implementation is undermined. The appropriate focus is on (for example) ‘participatory rural analysis’, ‘street-level bureaucracy’ and encouraging ‘public understanding of science’.

6. The problem can be defined as the ignorance of politicians about the existence of policy relevant research, or the incapacity of over-stretched bureaucrats to absorb research. The solution – ‘building bridges’ or constructing ‘conveyor belts’ – takes form, for example, of conferences and workshops, or the appointment of specialists to government committees

7. The problem can be conceived in terms of policy makers and leaders being dismissive, unresponsive or incapable of using research. This problem requires improvement in governmental capacity to recognise and absorb research, as well as in the capacities, personnel and resources of the state structure more generally.

8. The problem can be conceived of as not simply a question of research having a direct policy impact, but one of broader patterns of socio-political, economic and cultural influence. This leads to questioning of the domains of research relevance, impact and influence, and requires the adoption of a longer-term perspective where research may take a generation to exert real influence.

9. The problem can be defined as one of power relations. This generates concerns about the contested validity of knowledge(s), issues of censorship and control, and the question of ideology.

10. The problem can be viewed as one of the validity of research, and problems relating to the question: what is knowable? Attention is then focused on different epistemologies and ‘ways of knowing’.

Science-Policy Interaction in the context of ICZM

Science-policy interaction is essential for the implementation of Integrated Coastal Zone Management (ICZM). The ICZM Recommendation of the European Union states, as one of the eight principles of good ICZM: “Adaptive management during a gradual process which will facilitate adjustment as problems and knowledge develop. This implies the need for a sound scientific basis concerning the evolution of the coastal zone.” The Evaluation report of the ICZM Recommendation stresses the need for improving the knowledge base for ICZM and recommends “to provide guidance and develop human capacities through education and training and to support ICZM training centres, staff-exchange opportunities, university courses and advanced adult education”. Capacity building for educating coastal managers is substantiated in several Coastal Wiki articles, e.g. Capacity Building Needs Associated to the ICZM Cycle, Consultation on Maritime Policy: the issue of Capacity Building and Problem structuring in decision-making processes. However, the ten views above also point to a lack of policy awareness of researchers – an aspect that needs to be incorporated in Capacity Building programmes. The development of Decision support tools is an important step in bridging science and policy, although it should be recognized that the use of these systems in decision-making processes is still limited. The Coastal Wiki is another major effort to convey scientific insight to policy makers. The Main Page reminds authors that the Coastal Wiki is primarily meant for disseminating knowledge to a broader audience than the circles of specialists working at the frontiers of science. Many articles are written from a science perspective, though, and only a minority of articles is authored by policy makers. This can be seen as an illustration of the above views of research policy dynamic.

The main author of this article is Job Dronkers Please note that others may also have edited the contents of this article. Citation: Job Dronkers (2008): Science-Policy Interaction. Available from http://www.coastalwiki.org/wiki/Science-Policy_Interaction [accessed on 22-11-2024] For other articles by this author see Category:Articles by Job Dronkers For an overview of contributions by this author see Special:Contributions/Dronkers J