What are the next discoveries in evidence-informed decision-making? What kind of support do different societal stakeholders benefit from?
The Finnish science-policy ecosystem is pluralistic and de-centralised, consisting of a wide range of scientific research institutions, science brokers, and decision-makers utilising scientific knowledge.
The Finnish Academy of Science and Letters functions as a connecting hub within the national science-policy ecosystem. We build collaboration on several different levels, and with a wide range of stakeholders both among the scientific community and societal decision-makers.
Our central objective is better utilisation of high-quality research in decision-making, both within the government and a broader network of societal actors. We connect researchers with decision-makers and build new channels and tools for better societal dialogue.
We also actively represent the Finnish science-policy ecosystem in various international forums.
Our core activities in promoting evidence-informed decision-making:
- We support researchers in increasing the societal impact of their work.
- We work as a connecting hub by building new connections in the science-policy interface and facilitating the interaction among key stakeholders.
- We experiment and develop new operating models for better evidence-informed decision-making.
Guiding principles of our work:
- We facilitate the impact of scientific research through networks and partnerships.
- We focus on collating and brokering of existing high-quality scientific research.
- We build bridges and facilitate ongoing interaction among researchers and decision-makers.
- We promote the participation of young researchers and cross-organisational activities.
Since the establishment of the academy advancement of evidence-informed decision-making has been one of its core activities. The ongoing activities of the academy are built on the work of Sofi (Science Advice Initiative of Finland, 2019–2021), and presently our focus is on the development of several operating models, including Phenomena Maps, Impact Training Module, and Scientific Red Teams.