Abstract

This study explores the alignment of sustainable development and well-being agendas through semantic similarity analysis of textual documents. The aim is to evaluate how these agendas can be coherent and complementary. We employ advanced embedding techniques to transform political texts into numerical vectors, thereby allowing precise measurement of semantic proximity between different documents. The analysis reveals significant synergies between sustainable development goals and well-being measures beyond GDP. It also identifies potential areas of divergence that require specific attention. The findings underscore the importance of understanding and assessing the impact of development policies from an integrated perspective, aiming to optimize resources and promote sustainable and inclusive growth. This study demonstrates that advanced textual analysis can effectively guide policymakers towards better-informed and more effective strategies aligned with global sustainable development and well-being goals.