ArticleThe Journal of technology transfer2022
What semantic analysis can tell us about long term trends in the global STI policy agenda.
Article in The Journal of technology transfer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Asynchronous Cross-Modal Dynamic Graph Learning for Intelligent Sensing of AI Computing Infrastructure Expansion.Sensors (Basel, Switzerland) · 2026Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The scope, complexity and the "volume" of knowledge accumulated render producing an overview of the core themes of science, technology and innovation policies difficult. Reviews of this policy domain mostly either refer to general issues without deep immersion into details or focus on specific narrower aspects. The paper uses semantic analysis to identify major themes of science, technology and innovation policies over the last three decades and to trace their evolution towards current policy setting. We use semantic tools for processing and analysing documents produced by one of the major and highly reputable international expert bodies, the OECD Working Party on Technology and Innovation Policy. We show that selected themes remain in the mainstream even though being affected by regular policy adjustments and refinements and which disappear or appear with new challenges and expected solutions. Other themes appear niche or exotic themes which are under discussion for some time only.
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Registered trials
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