[Purpose/Significance] As scientific knowledge production shifts towards a problem-oriented paradigm, existing evaluation systems struggle to adequately assess interdisciplinary research and innovative value. To address these limitations, this study aims to construct a classification system for social science papers centered on ‘solving scientific problems,' thereby promoting a transformation in research evaluation towards an orientation of ‘effectiveness and contribution.' [Method/Process] Starting from the underlying logic of philosophy of science and following Thomas Kuhn's conventional theory of scientific development, this study proposes a four-category classification system for social science academic papers based on meta-research problems. At the same time, 1 125 journal papers from five typical social science sub-disciplines, namely political science, economics, management, sociology, and library and archive management, were selected as research objects from 2000 to 2020. Through multiple rounds of data annotation, automatic classification of academic papers was achieved based on SVM, XGBoost, BERT and other models, and the effectiveness of the classification method and discipline was tested. [Result/Conclusion] The results indicate that the four-category classification system based on meta-research questions has strong universality and practicality in social science research. In the future, further evaluation practices and research can be carried out based on this classification idea and related technologies.
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