Assessing a country ’s scientific contribution towards sustainability from higher education: a methodology for measuring progress towards the Sustainable Development Goals (SDG)
Resumen (es)
Objetivo. Desarrollar una metodología para evaluar la producción científica del país en relación con el cumplimiento de los Objetivos de Desarrollo Sostenible. Metodología. Se configuró un conjunto de datos de repositorios nacionales e internacionales de ciencia y tecnología donde se aloja la producción científica de Colombia; estos repositorios son reconocidos por alojar productos relacionados con las temáticas de los Objetivos de Desarrollo Sostenible. Como metodología se utilizó el análisis de redes complejas e indicadores como perplejidad y coherencia. Resultados. Entre los resultados más importantes destaca
la sincronización de productos científicos relacionados con los objetivos «Fin de la Pobreza», «Hambre Cero» y «Salud y Bienestar».
Se destaca la metodología utilizada como herramienta para analizar la producción científica de un país en relación con el cumplimiento de los objetivos de desarrollo sostenible.
Resumen (en)
Objective. To develop a methodology to evaluate the country’s scientific production regarding the fulfillment of the Sustainable Development Goals. Methodology. A data set of national and international repositories of science and technology where the scientific production of Colombia is housed was configured; these repositories are recognized for housing products related to the topics of the Sustainable Development Goals. Complex network analysis and indicators such as perplexity and coherence were used as methodology.Results. Among the most important results, the synchronization of scientific products related to the «End Poverty», «Zero Hunger» and «Health and Well-being» goals stands out. The methodology used as a tool to analyze the scientific production of a country regarding the fulfillment of the sustainable development goals is highlighted.
Resumen (pt)
Objectivo. Desenvolver uma metodologia para avaliar a produção científica do país em relação ao cumprimento dos Objectivos de
Desenvolvimento Sustentável. Metodologia. Foi configurado um conjunto de dados de repositórios nacionais e internacionais de
ciência e tecnologia onde se aloja a produção científica da Colômbia, reconhecidos por alojar produtos relacionados com os temas dos Objectivos de Desenvolvimento Sustentável. A metodologia utilizada foi a análise de redes complexas e indicadores como a perplexidade e a coerência. Resultados. Entre os resultados mais importantes, destaca-se a sincronização de produtos científicos relacionados com os objectivos «Acabar com a Pobreza», «Fome Zero» e «Saúde e Bemestar». Destaca-se a metodologia utilizada como ferramenta para analisar a produção científica de um país em relação ao cumprimento dos Objectivos de Desenvolvimento Sustentável.
Referencias
Sabina, A., Foster, J., Seth, S., Santos, A., Roche, J., and Ballon, P. (2015). Multidimensional poverty measurement and analysis. Oxford: Oxford University Press, USA. https:// ophi.org.uk/mpma-book-2015/
Blei, D., and Jordan, M. (2003). “Modeling annotated data”. In Proceedings of the 26th annual international ACM SIGIR conference on Research and development in information retrieval, 127-134. Association for Computing Machinery, New York, USA. https://doi.org/10.1145/860435.860460
Blei, D., Ng, A., and Jordan, M. (2003). “Latent Dirichlet Allocation”. The Journal of Machine Learning Research 3: 993-1022. https://dl.acm.org/doi/10.5555/944919.944937
Blesh, J., Hoey, L., Jones, A., Friedmann, H., and Perfecto, I. (2019). “Development pathways toward ‘zero hunger’”. World Development 118: 1-14. https://doi. org/10.1016/j.worlddev.2019.02.004
Coelho L., Peng, T., Murphy, R. (2010). “Quantifying the distribution of probes between subcellular locations using unsupervised pattern unmixing”. Bioinformatics, 26(12): i7-i12. https://doi.org/10.1093/bioinformatics/btq220
Cuesta, J., and Pico, J. (2020). “The gendered poverty effects of the COVID-19 pandemic in Colombia”. The European Journal of Development Research 32(5): 1558-91. https://doi.org/10.1057/s41287-020-00328-2
Departamento Nacional de Planeación. DNP. (2021). Documento CONPES 4069. Política Nacional de Ciencia, Tecnología e Innovación 2022-2031. https:// colaboracion.dnp.gov.co/CDT/Conpes/Econ %c3 %b3micos/4069.pdf
Diderichsen, F., Hallqvist, J., and Whitehead, M. (2019). “Differential vulnerability and susceptibility: how to make use of recent development in our understanding of mediation and interaction to tackle health inequalities”. International Journal of Epidemiology 48(1), 268-74. https://doi.org/10.1093/ije/dyy167
Duran, D., Artene, A., Gogan, L., and Duran, V. (2015). “The objectives of sustainable development-ways to achieve welfare”. Procedia Economics and Finance 26: 812- 817. https://doi.org/10.1016/S2212-5671(15)00852-7
Griffiths, T., and Mark, S. (2004). “Finding scientific topics”. The Proceedings of the National Academy of Sciences 101(Suppl 1):5228-35. https://doi.org/10.1073/ pnas.0307752101
Hernández Palma, H., Núñez, W., and Jiménez, M. (2019). “Sistema de salud colombiano: integración para la calidad”. Criterio Libre 18(31): 149-163. https:// doi.org/10.18041/1900-0642/criteriolibre.2019v18n31.6134
Hofmann, T. (1999). “Probabilistic latent semantic indexing”. Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval. 50-57. https://doi.org/10.1145/312624.312649
Hofmann, T. (2001). “Unsupervised learning by probabilistic latent semantic analysis”.
Machine Learning 42(1-2): 177-196. https://doi.org/10.1023/A:1007617005950
Hong, L., Frias-Martinez, E., and Frias-Martinez, V. (2016). “Topic models to infer socio-economic maps”. Thirtieth AAAI Conference on Artificial Intelligence 30(1): 3835-41. https://ojs.aaai.org/index.php/AAAI/article/view/9892.
Instituto Complutense de Estudios Internacionales. (2020). “Ciencia, tecnología e innovación para el cumplimiento de los objetivos de desarrollo sostenible en Iberoamérica”. https://www.ucm.es/data/cont/media/www/27289//Relatori %CC
%81a-CTI_12enero_2020.pdf
Jacobi, C., Atteveldt, W., and Welbers, K. (2016). “Quantitative analysis of large amounts of journalistic texts using topic modelling”. Digital Journalism, 4(1): 89- 106. https://doi.org/10.1080/21670811.2015.1093271
Khanal, U., Wilson, C., Sotavento, B., and Hoang, V. (2021). “Smallholder farmers’ adaptation to climate change and its potential contribution to UN’s sustainable development goals of zero hunger and no poverty”. Journal of Cleaner Production 281, 124999. https://doi.org/10.1016/j.jclepro.2020.124999
Manzano-Nunez, R., Sarmiento, C., Villegas-Vargas, S., Angel-Barrios, J., Puyana, J., Peck, G., Castro, F., Gaviria, A., García, A. (2022). “Emergency surgery workforce and its inverse relationship with multidimensional poverty in Colombia”. European Journal of Trauma and Emergency Surgery 48(2): 1159-1165. https:// doi.org/10.1007/s00068-021-01690-4
Mei, Q., Xu Shen, X., and Zhai, C. (2007). “Automatic labeling of multinomial topic models. In Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, 490-499. Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/1281192.1281246
Paul, M., and Dredze, M. (2013). “Drug extraction from the web: Summarizing drug experiences with multi-dimensional topic models”. In Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 168-178. Atlanta, Georgia. Association for Computational Linguistics.
Paul, M., and Dredze, M. (2014). “Discovering health topics in social media using topic models”. PloS One 9(8): e103408. https://doi.org/10.1371/journal.pone.0103408
Pinilla-Roncancio, M. (2018). “The reality of disability: Multidimensional poverty of people with disability and their families in Latin America”. Disability and Health Journal 11(3): 398-404. https://doi.org/10.1016/j.dhjo.2017.12.007
Ramage, D., Rosen, E., Chuang, J., Manning, C., and McFarland, A. (2009). “Topic modeling for the social sciences”. Workshop on applications for topic models NIPS 5: 1-4.
Ramírez, J., Díaz, Y., and Bedoya, J. (2017). “Property tax revenues and multidimensional poverty reduction in Colombia: A spatial approach”. World Development 94: 406- 421. https://doi.org/10.1016/j.worlddev.2017.02.005
Rentería-Ramos, R., Hurtado-Heredia, R., and Urdinola, P. (2019). “Morbi-Mortality of the Victims of Internal Conflict and Poor Population in the Risaralda Province, Colombia”. International Journal of Environmental Research and Public Health 16(9): 1644. https://doi.org/10.3390/ijerph16091644
Rogers S., Girolami, M., Campbell, C., Breitling R. (2005). “The latent process decomposition of cDNA microarray data sets”. IEEE/ACM transactions on computational biology and bioinformatics 2(2):143-56.
Roncancio, D., and Nardocci, A. (2020). “Social vulnerability in Colombia”. International Journal of Disaster Risk Reduction 50, 101872. https://doi.org/10.1016/j. ijdrr.2020.101872
Scimago. (2022). “Scimago Journal and Country Rank, 2019”. Last modified April, 2022. https://www.scimagojr.com/countryrank.php?year=2020
Shivashankar, S., Srivathsan, S., Ravindran, B., Tendulkar, A. (2011). “Multi-view methods for protein structure comparison using latent Dirichlet allocation”. Bioinformatics 27(13): i61-i68. https://doi.org/10.1093/bioinformatics/btr249
Stevens, K., Kegelmeyer, P., Andrzejewski, D., and Buttler, D. (2012). “Exploring topic coherence over many models and many topics”. In Proceedings of the 2012 joint conference on empirical methods in natural language processing and computational natural language learning, 952-961. Association for Computational Linguistics, USA.
Sunderland, T., O’Connor, A., Muir, G., Nerfa, L., Rota, G., Widmark, C., Bahar, N., and Ickowitz, A. (2019). “Zero hunger: Challenging the hegmony of monoculture agriculture for forests and people”. In Sustainable Development Goals: Their Impacts on Forests and People, Edited by Katila, P., Pierce, C., Jong, W., Galloway, G., Pacheco, P., and Winkel, G. 48-71. Cambridge: Cambridge University Press.
United Nations Educational, Scientific and Cultural Organization. (2017). La UNESCO Avanza. La Agenda 2030 para el Desarrollo Sostenible. Paris: UNESCO. https:// es.unesco.org/creativity/sites/creativity/files/247785sp_1_1_1.compressed.pdf.
Uribe-Tirado, A., Vallejo, J., y Betancur, D. (2016). “Somos visibles y tenemos impacto. Análisis desde datos de acceso abierto, altmetrics y otros de la Revista Interamericana de Bibliotecología”. Revista Interamericana de Bibliotecología 19(3): 243-75
Xin L., and Lei, L. (2021). “A bibliometric analysis of topic modelling studies (2000–2017)”. Journal of Information Science 47(2): 161-175. https://doi. org/10.1177/0165551519877049
Zhao, W., Chen, J., Perkins, R., Liu, Z., Ge, W., Ding, Y., and Zou, W. (2015). “A heuristic approach to determine an appropriate number of topics in topic modeling”. BMC bioinformatics 16(S8): 1-10. https://doi.org/10.1186/1471-2105-16-S13-S8
Cómo citar
Licencia
Derechos de autor 2023 Revista Interamericana de Investigación Educación y Pedagogía RIIEP

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.
Los autores mantienen los derechos sobre los artículos y por tanto son libres de compartir, copiar, distribuir, ejecutar y comunicar públicamente la obra bajo las condiciones siguientes:
Reconocer los créditos de la obra de la manera especificada por el autor o el licenciante (pero no de una manera que sugiera que tiene su apoyo o que apoyan el uso que hace de su obra).
RIIEP está bajo una licencia Creative Commons Atribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0)
La Universidad Santo Tomás conserva los derechos patrimoniales de las obras publicadas, y favorece y permite la reutilización de las mismas bajo la licencia anteriormente mencionada.