Dataset for "Generative AI and the Boundaries of Human Judgment" (Chinese HSS Reviewers）

This dataset supports the manuscript “Generative AI and the Boundaries of Human Judgment: A Study of Chinese HSS Reviewers in International Open‑Access Journals”. It contains richly annotated qualitative data illustrating how veteran Chinese humanities and social sciences (HSS) reviewers use generative AI tools during peer review.📄 Data Overview10 semi‑structured interviews (R1–R10), conducted in Mandarin between June 1–30, 2025Verbatim transcripts, back-translated into English for cross-cultural analysisCodebook (Appendix A): 202 initial codes linked to 4 core themes—Patterns of AI Use, Human Oversight & Quality Control, Disclosure & Governance, Ethical & Privacy ConcernsCoding-trail memo (Appendix B): shows how codes were clustered into subthemes and then into final themes using Braun & Clarke’s six-phase framework🛠️ Methods & EthicsParticipants: Experienced Chinese HSS peer reviewers with ≥10 international open-access reviewsData collection: Audio-recorded interviews, anonymized, IRB-approved, encrypted local storageAnalysis: Dual independent coding using NVivo 12 (Cohen’s κ = 0.82); thematic saturation reached by interview 10Verification: Triangulation across career stage and discipline to improve internal validity🔍 Research AimsInvestigate which review tasks prompt AI use (grammar, citations, structure, visualization)Understand layered verification habits—cross-platform checks, source tracing, expert consultationAnalyze how reviewers navigate cultural nuance, confidentiality, and disclosure given vague journal policies🌱 Reuse PotentialSupports replication in other cultural or disciplinary contextsEnables comparative studies of AI-assisted peer review practicesProvides a rich codebook for secondary thematic or discourse analysis📁 File Structurebash复制编辑/transcripts/ R1_Mandarin.txt R1_English.txt … (R1–R10) /codebook.xlsx /memo_coding_trail.pdfTranscripts labeled R1–R10, each with Mandarin and English versionscodebook.xlsx: lists 202 codes, subthemes, corresponding interview IDsmemo_coding_trail.pdf: documents thematic mapping process (Appendix B)🔐 Ethics & LicensingFully anonymized: no personal identifiers includedData collection followed IRB guidelines under [University Name]Licensed under CC BY 4.0Complies with Figshare’s human-subject data policies🔗 Related ResourcesArticle DOI: [to be populated upon acceptance]Supplementary materials (Appendix A & B) available via journal repository