Working Papers

This paper proposes the use of synthetic training data generated by large language models
to improve machine learning SDG classifiers. It shows that supplementing existing training data with
synthetic data produced by the ChatGPT tool improves the performance of the SDGClassy classifier.
This addition of synthetic data is especially useful in building SDG classifiers given the limited availability
of properly labeled data and the complex, interconnected nature of the SDGs. Synthetic data thus enables
more effective machine-learning applications in this context.

This paper conceptualizes recently negotiated international agreements, particularly the 2030 Agenda for Sustainable Development, as a collective roadmap to overcome challenges associated with globalization. By analyzing the effects and implications of globalization on societies and economies, the paper highlights concrete aspects of the international commitments that address globalization challenges in the three dimensions of sustainable development. Particular focus is placed on global production patterns, labor markets, poverty and inequality, global imbalances, migration and climate change. The paper concludes that, in the context of a changing political economy of globalization and…