Towards the Development of a Multidimensional Approach to Evaluating the Social Impact of Science: Integrating Alternative Metrics, Novel Indicators, and Artificial Intelligence

Abstract

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.