Author
Listed:
- Zhe Cao
- Lin Zhang
- Ying Huang
- Gunnar Sivertsen
Abstract
The importance of evidence‐based policymaking is widely recognized, but how science influences policy remains insufficiently explored. This study aims to examine how policy documents cite research articles, thereby tracing the complex impact process of scientific research on policymaking. A conceptual model is proposed to classify four types of citation pathways by distinguishing between direct and indirect impacts and observing whether a reinforcement effect is present. To operationalize this model, we collected nearly 10 thousand policy documents related to artificial intelligence (AI) and over 1.6 million links between these policies and their referenced articles. A large‐scale data analysis and a case study were conducted. Results exhibit distinct citation pathways among specific types of institutions, geopolitical areas, and policy areas. Indirect influences emerge as an important mechanism. Research articles from EU countries primarily serve the policymaking of inter‐governmental organizations (IGOs) and the EU, while research articles from the USA significantly support both domestic and foreign policymaking. Notably, IGOs serve as key intermediaries, facilitating the indirect influence of research on policymaking. In addition, while the knowledge from the social sciences provides substantial support for policies in various areas, an increasing involvement of the natural sciences in the development of AI‐related policies is found.
Suggested Citation
Zhe Cao & Lin Zhang & Ying Huang & Gunnar Sivertsen, 2025.
"How does scientific research influence policymaking? A study of four types of citation pathways between research articles and AI policy documents,"
Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 76(10), pages 1340-1356, October.
Handle:
RePEc:bla:jinfst:v:76:y:2025:i:10:p:1340-1356
DOI: 10.1002/asi.25006
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