HSSC_EGTC_Data_and_Supporting_Materials
Published: 1 July 2026| Version 1 | DOI: 10.17632/phk2k2mdvh.1
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Description
This dataset contains the methodological scripts and evaluation materials supporting the study "DeepResearch-Enhanced Grounded Theory Coding for Interdisciplinary Knowledge Analysis." The package includes Python scripts for the three-phase EGTC pipeline (Phase 1: parallel open and axial coding across three large language models; Phase 2: cross-model meta-coding and standardisation; Phase 3: DeepResearch-based selective coding), Python scripts for the three single-model baseline conditions (DeepSeek, Kimi, and Qwen one-shot workflows), a five-dimension expert blind evaluation form, and a blank semantic correspondence annotation table used for Fleiss' κ inter-annotator agreement assessment.
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Artificial Intelligence, Natural Language Processing