AI classification systems reshape understanding of public administration scholarship

A new study published on arXiv explores how different scholarly representation systems, including AI-assisted methods, classify public administration (PA) and AI-in-PA scholarship. The research found significant discrepancies in corpus size, publication types, and thematic structures across five distinct approaches, indicating that algorithmic knowledge organization actively shapes the understanding and boundaries of interdisciplinary fields. The findings emphasize that AI-driven classifications are interpretive and can influence disciplinary evolution, underscoring the continued importance of human judgment in complementing AI tools. AI

IMPACT Highlights how AI's role in classifying academic research can influence disciplinary boundaries and visibility.

RANK_REASON Academic paper analyzing AI's impact on scholarly classification. [lever_c_demoted from research: ic=1 ai=1.0]

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