Measuring Language and Source Bias in Global Cybersecurity Education Directories
Year: 2026
Type: preprint
Abstract: English preprint and reproducibility materials for a source-aware study of how language, query design, source architecture, temporal evidence, and counting unit affect the observed population of cybersecurity education programs. The record includes the English preprint, processed public research data, protocols, data dictionaries, case-study evidence, deterministic validation scripts, and SHA-256 checksums. It does not claim a complete world census or country rankings. Bulk third-party source captures are excluded because redistribution rights were not established.
Author: Pacheco, Federico
Institution: National Technological University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W7208832293
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