By Sylvain Perret
Director of Agrinatura
Representing Agrinatura at the recent Tropical Summit held in Lisbon (Nov. 5-7), I had the opportunity to partake in a panel discussion on agriculture, addressing the Science-Policy Divide for Sustainable Agricultural Development.
I chose to focus on one critical lesson from our collective Agrinatura works: policy-making is rarely based on scientific evidence. Our results and research outcomes hardly find their way towards concrete decisions and novel policies, norms, or regulations. Recent publications by Benton (2023; Nature Food) or Tuohy et al. (2023; Environmental Management) confirm such facts, and also the seminal works by Van den Hove (2007; Futures) on science-policy interfaces (SPI). According to these scholars, this disconnect arises because science and policy operate on fundamentally different cognitive and operational frameworks. Science relies on facts and rigorous methods, while policy is shaped by values, ideologies, beliefs, and political priorities.
More specific to Agrinatura’s work on complex agrifood systems, and their transformation, it is also noticeable that policymaking involves trade-offs and resource allocation decisions that are influenced by a combination of knowledge and value systems—often with limited scientific literacy among decision-makers. Policymakers prioritize scaling up solutions, often favoring “one-size-fits-all” approaches. Decisions tend to favor private and exclusive benefits over fostering public and common goods. These realities are intrinsic to the policy process and unlikely to change.
Agrinatura implements numerous R&D projects aimed at promoting sustainable agricultural development and transforming food systems. Some of these projects feature science-policy interfacing objectives. Through these projects (VCA4D, SASI-SPI, NRF, Desira-Lift, ERAIFT, CEA-First, for instance), we have identified strategies to better align scientific efforts with policy needs.
Here are four key approaches to catching and sustaining policy attention:
1. Engage Policy Actors Early: Involve policymakers at the outset of research design to co-develop projects that address societal challenges and drive impact. This includes translating challenges into research questions and hypotheses, developing theories of change, and incorporating foresight and modeling activities. Early and sustained engagement ensures relevance and facilitates buy-in.
2. Bridge and Pool Projects: While the project-based approach favored by donors will likely persist, researchers can enhance continuity by pooling related projects across different timeframes, disciplines, and geographic areas. Creating synergies among projects focused on similar challenges helps sustain attention and momentum among policymakers.
3. Focus on the Meso-Level: Effective dialogue and collaboration are often best achieved at the meso-level—value chains, territories, or regional systems—below the national level. These interventions provide opportunities for localized learning and adaptation, ultimately leading to better policy development.
4. Embed Policy Actors in Research Processes: Beyond communication and information transfer, policymakers can actively participate in research processes. Collaborative approaches, such as living labs, territorial foresight analyses, participatory impact assessments, and modeling, are particularly effective. These methods create a shared space for science-policy collaboration, enhancing mutual understanding and relevance.
To bridge the science-policy divide, we must do more and we must do things differently.
References
Benton, T.G., 2023. Academics can do more to disrupt and reframe the solution space for food system transformation. Nature Food, 4(11), pp.928-930.
Tuohy, P., Cvitanovic, C., Shellock, R.J., Karcher, D.B., Duggan, J. and Cooke, S.J., 2024. Considerations for research funders and managers to facilitate the translation of scientific knowledge into practice. Environmental Management, 73(3), pp.668-682.
Van den Hove, S., 2007. A rationale for science–policy interfaces. Futures, 39(7), pp.807-826.