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Research on climate policy is expanding rapidly, with around 85,000 studies published, a significant portion from 2020 onwards. A study from the Potsdam Institute for Climate Impact Research employs machine learning to analyze the distribution of this research by various factors, including country and policy level. This innovative approach highlights existing research gaps and provides a dynamic web tool for ongoing updates.
The study reveals that while major emitters like China and the U.S. receive substantial research attention, regions like Africa show a need for more insights. It also identifies a lack of research on regulatory instruments compared to economic ones, emphasizing the importance of understanding the interplay between different policy types. The continuous updates of the research map aim to support decision-makers in real-time, enhancing the effectiveness of climate policies.
• Machine learning identifies gaps in climate policy research distribution.
• Dynamic web tool provides real-time updates on climate policy studies.
Machine learning models are used to analyze and extract relevant information from climate policy studies.
Big data tools help manage and process the vast number of climate policy studies available.
Evidence synthesis summarizes existing knowledge for governments, aiding in informed decision-making.
The Potsdam Institute leads research on climate impact and employs machine learning to analyze climate policy literature.
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