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This paper applies InterCriteria Analysis (ICrA), grounded in intuitionistic fuzzy logic, to investigate the systemic inconsistencies among key indicators related to youth classified as NEET (Not in Employment, Education, or Training) within the European Union. Using Eurostat data from 2002 to 2023, the study focuses on multidimensional parameters such as urban-rural disparities, gender differences, educational attainment, and labor market participation. The intuitionistic fuzzy approach enables the detection of logical confirmation (μ), contradiction (ν), and hesitation (π) among criteria, offering a nuanced semantic interpretation beyond linear correlations. The results show a predominant concentration of country-pair evaluations in the dissonance zones, with over 88% falling into the “Dissonance” or “Strong Dissonance” categories, highlighting structural divergence among EU member states. The findings emphasize the limitations of universal policy solutions and the necessity for context-sensitive, data-driven interventions in tackling youth exclusion. ICrA proves to be a robust analytical tool for modeling complex socio-economic interdependencies and guiding evidence-based policymaking.

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InterCriteria Analysis of Youth Not in Employment, Education or Training in the EU: Revealing Structural Analysis Through Intuitionistic Fuzzy Evaluations

  • 会议论文

  • 发表日期：

    2026年

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  • Sotir Sotirov,
  • Rumiana Zheleva

摘要

This paper applies InterCriteria Analysis (ICrA), grounded in intuitionistic fuzzy logic, to investigate the systemic inconsistencies among key indicators related to youth classified as NEET (Not in Employment, Education, or Training) within the European Union. Using Eurostat data from 2002 to 2023, the study focuses on multidimensional parameters such as urban-rural disparities, gender differences, educational attainment, and labor market participation. The intuitionistic fuzzy approach enables the detection of logical confirmation (μ), contradiction (ν), and hesitation (π) among criteria, offering a nuanced semantic interpretation beyond linear correlations. The results show a predominant concentration of country-pair evaluations in the dissonance zones, with over 88% falling into the “Dissonance” or “Strong Dissonance” categories, highlighting structural divergence among EU member states. The findings emphasize the limitations of universal policy solutions and the necessity for context-sensitive, data-driven interventions in tackling youth exclusion. ICrA proves to be a robust analytical tool for modeling complex socio-economic interdependencies and guiding evidence-based policymaking.