Towards the Development of a Multidimensional Approach to Evaluating the Social Impact of Science: Integrating Alternative Metrics, Novel Indicators, and Artificial Intelligence
This thesis aims to explore emerging methodologies, metrics, parameters, and
indicators for assessing the societal impact of research, addressing the
limitations of traditional evaluation frameworks. As science policy increasingly
emphasises accountability, transparency, and public engagement, the
development of holistic assessment models becomes imperative. By examining
evolving approaches—including the integration of AI—this thesis aims to
contribute to the advancement of multidimensional frameworks that more
accurately capture the societal relevance of research. These insights are crucial
for informing funding allocation, institutional strategies, and policy
development, ensuring that research serves as a catalyst for effective societal
progress.
