IDEAS home Printed from https://ideas.repec.org/p/aue/wpaper/2538.html
   My bibliography  Save this paper

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

Author

Listed:
  • Phoebe Koundouri
  • Kostas Dellis
  • Monika Mavragani
  • Angelos Plataniotis
  • Georgios Feretzakis

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.

Suggested Citation

  • Phoebe Koundouri & Kostas Dellis & Monika Mavragani & Angelos Plataniotis & Georgios Feretzakis, 2025. "Do SDGs Support Human Security? A Machine Learning Analysis with Policy Recommendations," DEOS Working Papers 2538, Athens University of Economics and Business.
  • Handle: RePEc:aue:wpaper:2538
    as

    Download full text from publisher

    File URL: http://wpa.deos.aueb.gr/docs/2025.SDGs.Support.Human.Security.pdf
    File Function: First version
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aue:wpaper:2538. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ekaterini Glynou (email available below). General contact details of provider: https://edirc.repec.org/data/diauegr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.