When AI Classifies: What Counts as Public Administration?
This study examines how alternative systems of scholarly representation identify and characterize broad public administration (PA) and artificial intelligence related public administration (AI-in-PA) scholarship. Using Web of Science and OpenAlex, it compares five approaches based on author-defined, citation-driven, and AI-assisted representations. The results highlight substantial differences in corpus size, publication types, publishing outlets, temporal development, and thematic clustering and structure. The alternative approaches often identify different knowledge domains instead of varied subsets of the same scholarship and therefore produce distinct representations, as evidenced by ...
| Authors | Shaoming Cheng, Laurie Schintler |
|---|---|
| Primary category | cs.DL |
| Published | 26 June 2026 |
| Last updated at source | 26 June 2026 |
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