Dataset for: Generative AI and Student Freelancing: Skills, Income Opportunities, and Barriers in Somalia

This repository contains the underlying empirical survey dataset, variable codebook, and survey measurement instrument for the research article titled "Generative AI and Student Freelancing: Skills, Income Opportunities, and Barriers in Somalia" (F1000Research / Taylor & Francis Group, Manuscript ID: 193308). The study evaluates the structural relationships between Generative AI Competence (GAIC), Freelance Digital Skill Augmentation (FDSA), Platform Market Competitiveness (PMC), and Student Freelance Income Generation (SFIG), moderated by Structural, Financial, and Institutional Barriers (SFIB) based on N = 415 university student freelancers across Somalia. Files included in this repository:1. GenAI_Student_Freelancing_Somalia_Responses.csv: De-identified raw empirical dataset comprising 415 responses across 36 survey indicators.2. GenAI_Student_Freelancing_Somalia_Responses.xlsx: Formatted Microsoft Excel dataset containing two sheets: 'Survey_Responses_N415' (raw responses) and 'Codebook_Constructs' (variable dictionary and coding scale).3. GenAI_Student_Freelancing_Somalia_Codebook.pdf: Comprehensive 5-page standalone publication-grade reference codebook and measurement specifications manual.4. Questionnaire_Generative_AI_and_Student_Freelancing_Somalia.docx: Full bilingual (English and Somali) survey measurement instrument including ethics consent protocol (HIU-REC-2024-03).