ArticleFrontiers in research metrics and analytics2026
Trust, transparency, and disciplinary alignment in research funding evaluations: an illustrative case from the Norwegian AI Center call (2024-2025).
Article in Frontiers in research metrics and analytics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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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Abstract
The allocation of national AI Centers in June 2025 represents a significant research-policy investment in artificial intelligence in Norway. The broad call, which explicitly included artificial intelligence in the field of education, resulted in 50 applications from large consortia across disciplines and sectors, with an overall rejection rate of 88%. This entailed a substantial aggregate investment of resources across the university, higher education, and research institute sectors, thereby presupposing evaluation processes characterized by a high level of disciplinary expertise, transparency, fairness, and procedural integrity. This article examines the evaluation process associated with the AI Center call, using one application (DLCAIC) as an illustrative case, analyzed through the lens of procedural knowledge, domain-specific expertise, and established research on research evaluation. It explores whether an investment equivalent to approximately half a full-time work year in proposal development can generate meaningful reflection, learning, and improved proposal competence-provided that the evaluation feedback is thorough and well-substantiated, even for unsuccessful applicants. This article is not presented as a conventional empirical study, but as a research-informed
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