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Casquilho-Martins, I. & Lopes, A. L. (2026). How is social work research addressing the Sustainable Development Goals? A machine learning approach to tackling the 2030 Agenda. International Social Work,. https://doi.org/10.1177/00208728261501
I. C. Martins and A. L. Lopes, "How is social work research addressing the Sustainable Development Goals? A machine learning approach to tackling the 2030 Agenda", in Int. Social Work, 2026
@article{martins2026_1794066985050,
author = "Casquilho-Martins, I. and Lopes, A. L.",
title = "How is social work research addressing the Sustainable Development Goals? A machine learning approach to tackling the 2030 Agenda",
journal = "International Social Work",
year = "2026",
volume = "",
number = "",
doi = "10.1177/00208728261501",
url = "https://journals.sagepub.com/doi/10.1177/00208728261501875"
}
TY - JOUR TI - How is social work research addressing the Sustainable Development Goals? A machine learning approach to tackling the 2030 Agenda T2 - International Social Work AU - Casquilho-Martins, I. AU - Lopes, A. L. PY - 2026 SN - 0020-8728 DO - 10.1177/00208728261501 UR - https://journals.sagepub.com/doi/10.1177/00208728261501875 AB - Social work is increasingly engaging with the United Nations Sustainable Development Goals. The aim of this study is to analyse Sustainable Development Goals in social work research and identify their alignment with the 17 Sustainable Development Goals, using a machine learning text-classification approach on 4409 articles (2016–2024). Results show that social work research most frequently addresses reduced inequalities (Sustainable Development Goal 10), decent work and economic growth (Sustainable Development Goal 8), quality education (Sustainable Development Goal 4) and justice and strong institutions (Sustainable Development Goal 16), often in interconnected ways. In contrast, environmental goals are underrepresented. We discuss implications for broadening social work towards the full 2030 Agenda. ER -
English