From productivity to wellbeing? Topic modelling of doctoral education research

Higher Education. 2026. Vol. 91. No. 3. P. 993–1021.

Смирнов Н. М.

Doctoral education has undergone significant transformations over the past two decades, driven by massification, internationalization, and the diversification of training models. These shifts have led to a growing body of research on doctoral education, yet little is known about the overarching thematic and geographical trends shaping this field. This study applies computational natural language processing techniques, including topic modeling and Named Entity Recognition, to analyze 5593 research articles from the SCOPUS database published between 1998 and 2022. Our findings reveal two key insights. First, we identify a thematic shift in doctoral education research, with increasing emphasis on topics related to doctoral students’ well-being, identity, and experience, while earlier concerns about productivity and efficiency have declined. Second, we document a geographical imbalance in knowledge production, with the Global North dominating both authorship and empirical cases. The results contribute to ongoing discussions about the changing axiological landscape of doctoral education and the Eurocentric nature of global academic discourse. We discuss the methodological implications of our findings and highlight the need for further research into underrepresented perspectives.

Ключевые слова: topic modeling, knowledge production, Additive regularization for topic modeling, bibliometric data, doctoral education, Transformation of doctoral education, Academic dependency

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