Mapping the Landscape of SDG Research in Kazakhstan: A Machine Learning–Based Approach

Gulzhanat Gafu (), Daniel Hernández-Torrano, Nurgul Terlikbayeva and Anara Zhanseitova
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Gulzhanat Gafu: Nazarbayev University
Daniel Hernández-Torrano: Nazarbayev University
Nurgul Terlikbayeva: Nazarbayev University
Anara Zhanseitova: Nazarbayev University

Journal of the Knowledge Economy, 2025, vol. 16, issue 5, No 10, 15879-15904

Abstract: Abstract Research is critical in tackling the sustainable development goals (SDGs) particularly in the knowledge economy context, offering evidence-based solutions, monitoring advancements, and pinpointing hurdles. While scholars globally have extensively studied the SDGs, there is a notable gap in understanding SDG-related research in non-Global North contexts. This paper addresses this gap by examining the trajectory and current landscape of scholarly research addressing the SDGs in Kazakhstan. A total of 7092 Scopus-indexed Kazakhstani publications relevant to the SDGs from 2015 to 2023 were identified using a machine learning–based automated detection method to investigate the evolving trajectory of SDG-related publications over time and the predominant SDGs garnering the most research interest, to analyze the characteristics of knowledge production related to sustainable development, and the interconnectedness between SDGs in published works. While Kazakhstan’s engagement with SDGs reflects its commitment to the knowledge economy, especially in sustainable development research, the results show that the relative growth of SDG-related publications in Kazakhstan has declined by 10% in the last seven years. Moreover, publications addressing SDGs exhibit a statistically lower rate of international collaboration, are less available open access, and receive less funding than publications not addressing the SDGs. The study highlights that there is significant variation in the scholarly attention given to different SDGs: SDGs 7, 8, 10, 3, and 4 received the most attention, while the least attention was directed toward SDGs 1, 5, 14, and 17. Our analysis also revealed multiple synergies between certain SDGs that are thematically aligned and particularly relevant within the context of Kazakhstan. The findings are discussed, and implications for sustainable development research and the achievement of the SDGs in Kazakhstan and beyond are presented.

Keywords: Sustainability; Sustainable development goals; SDG; Knowledge economy; Research; Central Asia; Machine learning; Mapping (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s13132-024-02543-2

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