Using Digital Tools to Understand Global Development Continuums

Traditional classifications of global development, such as the developed/developing dichotomy or Global North/South, often oversimplify the intricate landscape of human development. This paper leverages computational tools, advanced visualization techniques, and mathematical modeling to challenge th...

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Main Authors: J. de Curtò, I. de Zarzà
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Societies
Subjects:
Online Access:https://www.mdpi.com/2075-4698/15/3/65
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author J. de Curtò
I. de Zarzà
author_facet J. de Curtò
I. de Zarzà
author_sort J. de Curtò
collection DOAJ
description Traditional classifications of global development, such as the developed/developing dichotomy or Global North/South, often oversimplify the intricate landscape of human development. This paper leverages computational tools, advanced visualization techniques, and mathematical modeling to challenge these conventional categories and reveal a continuous development spectrum among nations. By applying hierarchical clustering, multidimensional scaling, and interactive visualizations to Human Development Index (HDI) data, we identify “development neighborhoods”—clusters of countries that exhibit similar development patterns, sometimes across geographical boundaries. Our methodology combines network theory, statistical physics, and digital humanities approaches to model development as a continuous field, introducing novel metrics for development potential and regional inequality. Through analysis of HDI data from 193 countries (1990–2022), we demonstrate significant regional variations in development trajectories, with Africa showing the highest mean change rate (28.36%) despite maintaining the lowest mean HDI (0.557). The implementation of circle packing and radial dendrogram visualizations reveals both population dynamics and development continuums, while our mathematical framework provides rigorous quantification of development distances and cluster stability. This approach not only uncovers sophisticated developmental progressions but also emphasizes the importance of continuous frameworks over categorical divisions. The findings highlight how digital humanities tools can enhance our understanding of global development, providing policymakers with insights that traditional methods might overlook. Our methodology demonstrates the potential of computational social science to offer more granular analyses of development, supporting policies that recognize the diversity within regional and developmental clusters, while our mathematical framework provides a foundation for future quantitative studies in development economics.
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spelling doaj-art-0cab174f4c1b41aeb4f09368fa04ed002025-08-20T02:43:07ZengMDPI AGSocieties2075-46982025-03-011536510.3390/soc15030065Using Digital Tools to Understand Global Development ContinuumsJ. de Curtò0I. de Zarzà1Department of Computer Applications in Science & Engineering, BARCELONA Supercomputing Center, 08034 Barcelona, SpainEstudis d’Informàtica, Multimèdia i Telecomunicació, Universitat Oberta de Catalunya, 08018 Barcelona, SpainTraditional classifications of global development, such as the developed/developing dichotomy or Global North/South, often oversimplify the intricate landscape of human development. This paper leverages computational tools, advanced visualization techniques, and mathematical modeling to challenge these conventional categories and reveal a continuous development spectrum among nations. By applying hierarchical clustering, multidimensional scaling, and interactive visualizations to Human Development Index (HDI) data, we identify “development neighborhoods”—clusters of countries that exhibit similar development patterns, sometimes across geographical boundaries. Our methodology combines network theory, statistical physics, and digital humanities approaches to model development as a continuous field, introducing novel metrics for development potential and regional inequality. Through analysis of HDI data from 193 countries (1990–2022), we demonstrate significant regional variations in development trajectories, with Africa showing the highest mean change rate (28.36%) despite maintaining the lowest mean HDI (0.557). The implementation of circle packing and radial dendrogram visualizations reveals both population dynamics and development continuums, while our mathematical framework provides rigorous quantification of development distances and cluster stability. This approach not only uncovers sophisticated developmental progressions but also emphasizes the importance of continuous frameworks over categorical divisions. The findings highlight how digital humanities tools can enhance our understanding of global development, providing policymakers with insights that traditional methods might overlook. Our methodology demonstrates the potential of computational social science to offer more granular analyses of development, supporting policies that recognize the diversity within regional and developmental clusters, while our mathematical framework provides a foundation for future quantitative studies in development economics.https://www.mdpi.com/2075-4698/15/3/65digital humanitiesHuman Development Indexhierarchical clusteringdevelopment continuumvisualizationcomputational social science
spellingShingle J. de Curtò
I. de Zarzà
Using Digital Tools to Understand Global Development Continuums
Societies
digital humanities
Human Development Index
hierarchical clustering
development continuum
visualization
computational social science
title Using Digital Tools to Understand Global Development Continuums
title_full Using Digital Tools to Understand Global Development Continuums
title_fullStr Using Digital Tools to Understand Global Development Continuums
title_full_unstemmed Using Digital Tools to Understand Global Development Continuums
title_short Using Digital Tools to Understand Global Development Continuums
title_sort using digital tools to understand global development continuums
topic digital humanities
Human Development Index
hierarchical clustering
development continuum
visualization
computational social science
url https://www.mdpi.com/2075-4698/15/3/65
work_keys_str_mv AT jdecurto usingdigitaltoolstounderstandglobaldevelopmentcontinuums
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