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Supplementary datasets S1–S4 for "Cognitive Warfare Through the Tool: Generative AI, Epistemic Security and the Unregulated Layer of Professional Military Education in Ukraine"

Year: 2026
Type: supplementary-materials
Abstract: Supplementary datasets for the article “Cognitive Warfare Through the Tool: Generative AI, Epistemic Security and the Unregulated Layer of Professional Military Education – Evidence from Ukraine” (manuscript under review). S1 – Expert assessment: survey instrument (Ukrainian original) with an English variable codebook and anonymised ratings of twelve Ukrainian defence practitioners (12 respondents × 53 items; November 2025). Respondents are identified only by codes R01–R12. S2 – Document analysis: sixteen-item codebook (v2) with decision rules; pilot calibration (two LLM-assisted passes verified by the first author); two independent codings of five institutional AI policies; agreed coding and conservative re-reading; script computing Cohen's κ (κ = 0.92, κw = 0.95). S3 – Scenario model: Python code of the multiplicative risk model with non-parametric bootstrap (20,000 iterations, fixed seed); attribution matrix; results for three threat scenarios and three assumptions about the effectiveness of curricular measures; sensitivity analysis (Spearman ρ). S4 – Bibliometrics: Scopus and Lens.org search strings (retrieved 25–26 August 2026); VOSviewer thesaurus (134 merge rules, 76 removed generic index terms); VOSviewer map and network files for corpora C1, C1-core, C2, C3 and the combined Scopus–Lens.org term map; tables A–H; bibliographic records of the fourteen documents in Supplementary Table B1. All files are described in README.md, which also maps file names to the table and figure numbering of the version under review. Data collection was anonymous and voluntary; no personal data beyond professional category, experience and self-rated AI familiarity were collected. Version 2.0.0: metadata corrected (author list, order and ORCID identifiers; title; thesaurus counts); data archives unchanged from version 1.0.0.
Language: English
Open Access status: green
OpenAlex ID: W7204852272
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