000151469 001__ 151469
000151469 005__ 20250310131043.0
000151469 0247_ $$2doi$$a10.3390/soc15030065
000151469 0248_ $$2sideral$$a143151
000151469 037__ $$aART-2025-143151
000151469 041__ $$aeng
000151469 100__ $$ade Curtò, J.
000151469 245__ $$aUsing Digital Tools to Understand Global Development Continuums
000151469 260__ $$c2025
000151469 5060_ $$aAccess copy available to the general public$$fUnrestricted
000151469 5203_ $$aTraditional 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.
000151469 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000151469 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000151469 700__ $$0(orcid)0000-0002-5844-7871$$ade Zarzà, I.$$uUniversidad de Zaragoza
000151469 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf.
000151469 773__ $$g15, 3 (2025), 65 [26 pp.]$$pSocieties (Basel)$$tSocieties (Basel)$$x2075-4698
000151469 787__ $$tInteractive circle packing visualization, representing global population distribution (2023)$$tInteractive radial dendrogram visualization, illustrating hierarchical clustering of the Human Development Index (HDI) (2022)$$whttps://public.flourish.studio/visualisation/20110969/$$whttps://public.flourish.studio/visualisation/20112689/
000151469 8564_ $$s10622050$$uhttps://zaguan.unizar.es/record/151469/files/texto_completo.pdf$$yVersión publicada
000151469 8564_ $$s2485410$$uhttps://zaguan.unizar.es/record/151469/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000151469 909CO $$ooai:zaguan.unizar.es:151469$$particulos$$pdriver
000151469 951__ $$a2025-03-10-12:56:20
000151469 980__ $$aARTICLE