Uncovering the SDG content of Human Security Policies through a Machine Learning web application

Koundouri, Phoebe and Aslanidis, Panagiotis-Stavros and Dellis, Konstantinos and Feretzakis, Georgios and Plataniotis, Angelos (2024): Uncovering the SDG content of Human Security Policies through a Machine Learning web application. Published in:

Abstract

This paper introduces a machine learning (ML) based approach for integrating Human Security (HS) and Sustainable Development Goals (SDGs). Originating in the 1990s, HS focuses on strategic, people-centric interventions for ensuring comprehensive welfare and resilience. It closely aligns with the SDGs, together forming the foundation for global sustainable development initiatives. Our methodology involves mapping 44 reports to the 17 SDGs using expert-annotated keywords and advanced ML techniques, resulting in a web-based SDG mapping tool. This tool is specifically tailored for the HS-SDG nexus, enabling the analysis of 13 new reports and their connections to the SDGs. Through this, we uncover detailed insights and establish strong links between the reports and global objectives, offering a nuanced understanding of the interplay between HS and sustainable development. This research provides a scalable framework to explore the relationship between HS and the Paris Agenda, offering a practical, efficient resource for scholars and policymakers.

• Item Type: MPRA Paper
• Language: English
• Keywords: Artificial Intelligence in Policy Making, Data Mining, Human-Centric Governance Strategies, Human Security, Machine Learning, Sustainable Development Goals
• Subjects: C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C65 - Miscellaneous Mathematical Tools; O - Economic Development, Innovation, Technological Change, and Growth > O1 - Economic Development > O15 - Human Resources ; Human Development ; Income Distribution ; Migration

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