Lost in translation: Bridging science and EU policy

As part of its ethical, cultural, and societal values, the European Union has, for decades, embraced the aspiration to base political decisions on scientific evidence¹. Prime examples include the European Green Deal, and the climate and biodiversity targets underpinned by science broadly, and specifically by the IPCC and IPBES, along with numerous processes for open consultation and evidence gathering. Also, an internal mechanism called “Feedback to Policy” exists, designed to “bridge policy work and research stemming from Horizon Europe via collaborative channels and work between policy DGs and executive agencies” (EC, 2025). This encompasses diverse dissemination activities whose success or failure driving factors are shared with other process of this nature.

Various mechanisms have been evaluated to enhance the knowledge transfer from science to policymaking, revealing factors contributing to both success and failure. In both national and EU contexts, knowledge brokers have emerged as pivotal figures in bridging the science-to-policy gap. Additionally, high level of co-creation is considered a success factor (Sienkiewicz and Mair, 2020), while sector-specific independent advisory boards and working groups with consolidated participation from both policymakers and researchers can achieve considerable influence. Also, the inclusion of Social Sciences and Humanities (SSH) experts within research teams, alongside basic scientific competencies from policymakers, serves as a crucial enabler. For that reason, many of the recommended practices include actions to improve capacity in both the policy and research institutions (Topp et al., 2018).

Evidence has also highlighted factors that facilitate the failure of science-to-policy transfer, such as gaps between researchers and policymakers across various levels, together with institutional, normative, and operational aspects, and those related to co-creation and evaluation and learning processes (EC-JRC, 2024). Regarding the first aspect, the mismatch between what science can deliver and policymaker expectations can be significant due to differing timelines, miscommunication, and uncertainty mismanagement, among other aspects. Human factors play a critical role here in establishing genuine relationships that allows effective message orientation and trust-building. On a more operational level, an inadequate design of knowledge transfer and communication actions can pave the way for failure. Finally, concerning evaluation and learning, there is a prevalent absence of post-assessment and failure attribution mechanisms necessary to understand why and where within the decision chain policy diverges from scientific evidence. In domains like climate and biodiversity, decisions and legislation undergo intense political negotiation, where diverse layers of information and powerful non-scientific factors may divert political decision-making from the purely technical or scientific optimum. Establishing transparent evaluation mechanisms to assess how knowledge is adopted in policymaking would be a crucial step to optimise the transfer we aspire to achieve.

¹https://commission.europa.eu/law/law-making-process/better-regulation_en#:~:text=In%20this%20context%2C%20the%20better,managing%20and%20evaluating%20existing%20legislation.

References

EC, 2025.  Interim Evaluation of the Horizon Europe Framework Programme for Research and Innovation (2021 - 2024). SWD (2025) 110 final.

EC- JRC, 2024. Science-for-policy ecosystems through the eyes of professionals, Publications Office of the European Union, Luxembourg, 2024, JRC139213.

Sienkiewicz, M,  Mair, D, .2020. Against the Science–Policy Binary Separation: Science for Policy 1.0. 10.1016/b978-0-12-822596-7.00001-2.

Topp, L., Mair, D., Smillie, L. et al. Knowledge management for policy impact: the case of the EC’s JRCe. Palgrave Commun 4, 87 (2018).