Do SDGs Support Human Security? A Machine Learning Analysis with Policy Recommendations

Phoebe Koundouri (), Kostas Dellis, Monika Mavragani, Angelos Plataniotis and Georgios Feretzakis

No 2538, DEOS Working Papers from Athens University of Economics and Business

Abstract: Human Security (HS) emphasizes safeguarding individuals from pervasive threats-ranging from poverty and health crises to environmental degradation and governance failures-by placing people's rights, needs, and dignity at the center of security and development discourse. The Sustainable Development Goals (SDGs), serving as a global compass for equitable and sustainable progress, inherently support the well-being and resilience of people worldwide. Yet the explicit linkages between these two frameworks are not always clear. This chapter introduces a machine learning (ML) approach to systematically map how HS-related policy documents and reports align with the SDGs. Using advanced language-model embeddings and similarity scoring, our methodology identifies the extent to which each policy text addresses defined HS Aspects and their Material Issues. This allows us to move beyond simple keyword spotting toward capturing nuanced thematic alignment. The resulting scores highlight overlooked connections or synergies, enabling policymakers to see where further integration can enhance outcomes. Our mapping exercise revealed that Economic and Food Security achieved the highest similarity scores, indicating robust policy alignment. Conversely, Technological Security received lower scores, highlighting a gap in addressing digital and innovation challenges within current frameworks and the necessity for integrated policy solutions. By identifying thematic synergies and gaps, we provide policymakers with concrete insights delineate policies that simultaneously enhance SDG outcomes and strengthen HS dimensions. Our results underscore the deep interconnection between HS and the SDGs, advancing our understanding of their mutual supportiveness. This study not only fills a critical gap in research by offering a pragmatic tool for assessing document alignment with the SDGs but also proposes an inclusive framework for policymakers and scholars. This framework encourages the integration of human-centered approaches with sustainable development goals. In doing so, it highlights the essential role of cutting-edge methodologies in navigating the complexities of global security and sustainability.

Keywords: Human Security (HS); Sustainable Development Goals (SDGs); Machine Learning; Economic Policy; Textual Analysis (search for similar items in EconPapers)
Date: 2025-05-29
New Economics Papers: this item is included in nep-big
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