Natural language processing and network analysis provide novel insights on policy and scientific discourse around Sustainable Development Goals – Scientific Reports
United Nations. Transforming Our World: The 2030 Agenda for Sustainable Development. https://undocs.org/en/A/70/L.1 (2016).
Tosun, J. & Leininger, J. Governing the interlinkages between the Sustainable Development Goals: Approaches to attain policy integration. Glob. Challenges 1, 1700036 (2017).
Fuso Nerini, F. et al. Connecting climate action with other Sustainable Development Goals. Nat. Sustain. 2, 674680 (2019).
Collste, D., Pedercini, M. & Cornell, S. E. Policy coherence to achieve the SDGs: Using integrated simulation models to assess effective policies. Sustain. Sci. 12, 921931 (2017).
Google Scholar
Breuer, A., Janetschek, H. & Malerba, D. Translating sustainable development goal (SDG) interdependencies into policy advice. Sustainability 11, 2092 (2019).
Le Blanc, D. Towards integration at last? The Sustainable Development Goals as a network of targets. Sustain. Dev. 23, 176187 (2015).
Nilsson, M., Griggs, D. & Visbeck, M. Policy: Map the interactions between Sustainable Development Goals. Nature 534, 320322 (2016).
Google Scholar
Allen, C., Metternicht, G. & Wiedmann, T. Prioritising SDG targets: Assessing baselines, gaps and interlinkages. Sustain. Sci. 14, 421438 (2019).
Bennich, T., Weitz, N. & Carlsen, H. Deciphering the scientific literature on SDG interactions: A review and reading guide. Sci. Total Environ. 728, 138405 (2020).
Google Scholar
Editorial: Get the Sustainable Development Goals Back on Track. Nature https://www.nature.com/articles/d41586-019-03907-4 (2020).
Scharlemann, J. P. W. et al. Towards understanding interactions between Sustainable Development Goals: The role of environmenthuman linkages. Sustain. Sci. 15, 15731584 (2020).
Messerli, P. et al. Global Sustainable Development Report 2019: The Future is NowScience for Achieving Sustainable Development. (United Nations, 2019).
Mihalcea, R. & Tarau, P. TextRank: Bringing Order into Texts. https://www.aclweb.org/anthology/W04-3252 (2004).
Blei, D. M., Ng, A. Y. & Edu, J. B. Latent Dirichlet allocation Michael I. Jordan. J. Mach. Learn. Res. 3, 9931022 (2003).
Le, Q. V. & Mikolov, T. Distributed representations of sentences and documents. in 31st International Conference on Machine Learning, ICML 2014. Vol. 4. 29312939 (International Machine Learning Society (IMLS), 2014).
Niestroy, I. How Are We Getting Ready? The 2030 Agenda for Sustainable Development in the EU and Its Member States: Analysis and Action So Far. (German Development Institute, 2016).
Raworth, K. Doughnut Economics: Seven Ways to Think Like a 21st-Century Economist. (Chelsea Green, 2017).
TWI2050The World in 2050. Innovations for Sustainability. Pathways to an Efficient and Post-Pandemic Future. Report Prepared by The World in 2050 Initiative. https://doi.org/10.22022/TNT/07-2020.16533 (2020).
Alcamo, J. et al. Analysing interactions among the Sustainable Development Goals: Findings and emerging issues from local and global studies. Sustain. Sci. 15, 15611572 (2020).
International Council for Science. A Guide to SDG Interactions: From Science to Implementation. https://council.science/publications/a-guide-to-sdg-interactions-from-science-to-implementation/. https://doi.org/10.24948/2017.01 (2017).
Pham-Truffert, M., Metz, F., Fischer, M., Rueff, H. & Messerli, P. Interactions among Sustainable Development Goals: Knowledge for identifying multipliers and virtuous cycles. Sustain. Dev. 28, 12361250 (2020).
Pradhan, P., Costa, L., Rybski, D., Lucht, W. & Kropp, J. P. A systematic study of sustainable development goal (SDG) interactions. Earths Future 5, 11691179 (2017).
Google Scholar
Pedercini, M., Arquitt, S., Collste, D. & Herren, H. Harvesting synergy from sustainable development goal interactions. Proc. Natl. Acad. Sci. U. S. A. 116, 2302123038 (2019).
Google Scholar
Lusseau, D. & Mancini, F. Estimating the sustainome income-based variation in sustainable development goal interaction networks. Nat. Sustain. 2, 242247 (2019).
Asadikia, A., Rajabifard, A. & Kalantari, M. Systematic prioritisation of SDGs: Machine learning approach. World Dev. 140, 105269 (2021).
Hegre, H., Petrova, K. & Von Uexkull, N. Synergies and trade-offs in reaching the Sustainable Development Goals. Sustainability 12, 8729 (2020).
Zhou, X., Moinuddin, M. & Xu, Z. Sustainable Development Goals Interlinkages and Network Analysis: A Practical Tool for SDG Integration and Policy Coherence. (Institute for Global Environmental Strategies (IGES), 2017).
Kroll, C., Warchold, A. & Pradhan, P. Sustainable development goals (SDGs): Are we successful in turning trade-offs into synergies?. Palgrave Commun. 5, 111 (2019).
Capua, I. & Giovannini, E. Coding system to track research progress towards SDGs. Nature 572, 178 (2019).
Google Scholar
Fuso Nerini, F. et al. Mapping synergies and trade-offs between energy and the Sustainable Development Goals. Nat. Energy 3, 1015 (2017).
Google Scholar
Shrivastava, P., Stafford Smith, M., OBrien, K. & Zsolnai, L. Transforming sustainability science to generate positive social and environmental change globally. One Earth 2, 329340 (2020).
Smith, T. B., Vacca, R., Krenz, T. & McCarty, C. Great minds think alike, or do they often differ? Research topic overlap and the formation of scientific teams. J. Informetric 15, 101104 (2021).
Guimer, R., Uzzi, B., Spiro, J. & Nunes Amaral, L. A. Team assembly mechanisms determine collaboration network structure and team performance. Science 308, 697702 (2005).
Google Scholar
Jones, B. F., Wuchty, S. & Uzzi, B. Multi-university research teams: Shifting impact, geography, and stratification in science. Science 322, 12591262 (2008).
Google Scholar
Fortunato, S. et al. Science of science. Science (80-) 359, eaao185 (2018).
ECOSOC. Progress Towards the Sustainable Development GoalsReport of the Secretary-General. https://undocs.org/en/E/2020/57 (2020).
Straka, M. & Strakov, J. Tokenizing, POS tagging, lemmatizing and parsing UD 2.0 with UDPipe. in CoNLL 2017-SIGNLL Conference on Computational Natural Language Learning, Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies. 8899. https://doi.org/10.18653/v1/k17-3009 (Association for Computational Linguistics (ACL), 2017).
Mikolov, T., Sutskever, I., Chen, K., Corrado, G. & Dean, J. Distributed representations of words and phrases and their compositionality. in Advances in Neural Information Processing Systems 26 (NIPS 2013) (Neural Information Processing Systems Foundation, 2013).
Srensen, T. A method of establishing groups of equal amplitude in plant sociology based on similarity of species and its application to analyses of the vegetation on Danish commons. Biol. Skr. Danske Vidensk. Selsk. 5, 134 (1948).
Blondel, V. D., Guillaume, J. L., Lambiotte, R. & Lefebvre, E. Fast unfolding of communities in large networks. J. Stat. Mech. Theory Exp. 2008, P10008 (2008).
Google Scholar
Webster, K. et al. Contextualizing sustainable development research using dimensions to explore the global landscape of research on Sustainable Development Goals. Digit. Sci. https://doi.org/10.6084/m9.gshare.12200081 (2020).
Google Scholar
Chung, N. C., Miasojedow, B., Startek, M. & Gambin, A. Jaccard/Tanimoto similarity test and estimation methods. BMC Bioinform. 20, 644 (2019).
Hausser, J., Ch, J. H. & De, S.-L. Entropy inference and the James-Stein estimator, with application to nonlinear gene association networks Korbinian strimmer. J. Mach. Learn. Res. 10, 14691484 (2009).
Google Scholar
Newman, M. E. J. Mixing patterns in networks. Phys. Rev. E Stat. Physics Plasmas Fluids Relat. Interdiscip. Top. 67, 026126 (2002).
United Nations. The Millenium Development Goals Report 2015. https://www.un.org/millenniumgoals/2015_MDG_Report/pdf/MDG2015rev(July1).pdf (2015).
Editorial: Time to Revise the Sustainable Development Goals. Nature https://www.nature.com/articles/d41586-020-02002-3 (2020).
Xu, Z. et al. Assessing progress towards sustainable development over space and time. Nature 577 (2020).
Kluge, H. H. P. & Monti, M. Rethinking Policy Priorities in the Light of Pandemics: A Call to Action. https://www.euro.who.int/__data/assets/pdf_file/0010/495856/Pan-European-Commission-Call-to-action-eng.pdf (2021).
Rao, A. & Kelleher, D. Institutions, organisations and gender equality in an era of globalisation. Gend. Dev. 11, 142149 (2003).
Duflo, E. Women empowerment and economic development. J. Econ. Lit. 50, 10511079 (2012).
Kabeer, N. Gender equality, economic growth, and womens agency: The endless variety and monotonous similarity of patriarchal constraints. Fem. Econ. 22, 295321 (2016).
Connor, J. et al. Health risks and outcomes that disproportionately affect women during the Covid-19 pandemic: A review. Soc. Sci. Med. 266, 113364 (2020).
Sevilla, A. & Smith, S. Baby steps: The gender division of childcare during the COVID-19 pandemic. Oxf. Rev. Econ. Policy 36, S169S186 (2020).
Cajner, T. et al. The U.S. Labor Market during the Beginning of the Pandemic Recession. http://www.nber.org/papers/w27159.pdf. https://doi.org/10.3386/w27159 (2020).
Adams-Prassl, A., Boneva, T., Golin, M. & Rauh, C. Inequality in the impact of the coronavirus shock: Evidence from real time surveys. J. Public Econ. 189, 104245 (2020).
Huber, J. D. & Mayoral, L. Group inequality and the severity of civil conflict. J. Econ. Growth 24, 141 (2019).
Gutirrez-Romero, R. How does inequality affect long-run growth? Cross-industry, cross-country evidence. Econ. Model. 95, 274297 (2021).
Berg, A., Ostry, J. D., Tsangarides, C. G. & Yakhshilikov, Y. Redistribution, inequality, and growth: New evidence. J. Econ. Growth 23, 259305 (2018).
Fouad, F. M. et al. Health workers and the weaponisation of health care in Syria: A preliminary inquiry for The Lancet-American University of Beirut Commission on Syria. Lancet 390, 25162526 (2017).
Google Scholar
Pannu, J. & Barry, M. The state inoculates: Vaccines as soft power. Lancet Glob. Heal. 9, e744e745 (2021).
Deaton, A. The Great Escape: Health, Wealth, and the Origins of Inequality. (Princeton University Press, 2013).
Bloom, D., Canning, D., Kotschy, R., Prettner, K. & Schnemann, J. Health and Economic Growth: Reconciling the Micro and Macro Evidence. http://www.nber.org/papers/w26003.pdf. https://doi.org/10.3386/w26003 (2019).
Acemoglu, D. & Johnson, S. Disease and development: The effect of life expectancy on economic growth. J. Polit. Econ. 115, 925985 (2007).
Cervellati, M. & Sunde, U. Life expectancy and economic growth: The role of the demographic transition. J. Econ. Growth 16, 99133 (2011).
Barofsky, J., Anekwe, T. D. & Chase, C. Malaria eradication and economic outcomes in sub-Saharan Africa: Evidence from Uganda. J. Health Econ. 44, 118136 (2020).
Talukdar, D., Seenivasan, S., Cameron, A. J. & Sacks, G. The association between national income and adult obesity prevalence: Empirical insights into temporal patterns and moderators of the association using 40 years of data across 147 countries. PLoS One 15, e0232236 (2020).
Lange, S. & Vollmer, S. The effect of economic development on population health: A review of the empirical evidence. Br. Med. Bull. 121, 4760 (2017).
Google Scholar
Leifeld, P. Policy debates and discourse network analysis: A research agenda. Polit. Gov. 8, 180183 (2020).
Sun, C., Huang, L. & Qiu, X. Utilizing BERT for aspect-based sentiment analysis via constructing auxiliary sentence. in NAACL HLT 20192019 Conference North American Chapter Association for Computational Linguistics Human Language TechnologyProceeding Conference. Vol. 1. 380385 (2019).
Warchold, A., Pradhan, P. & Kropp, J. P. Variations in sustainable development goal interactions: Population, regional, and income disaggregation. Sustain. Dev. 29, 285299 (2021).