Youth Apprentice Vulnerability Classifier: AI-Driven Risk Profiling System

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Authors: Daniel Thomaz Giacomelli Nunes Maciel, Arturo Alejandro Zavala Zavala
Cited by: 0

Abstract

Specialized SKILL for Youth Employment Program Risk Assessment This computational tool provides automated vulnerability classification for young apprentices in workforce development programs, enabling targeted support allocation and dropout prevention strategies. Core Capabilities: Multi-factor vulnerability scoring (family income, educational background, geographic isolation, disability status); risk stratification into intervention priority levels; automated report generation for case managers; longitudinal tracking support for program outcomes. Potential Impact: Can enhance efficiency of youth employment programs by identifying high-risk participants who may benefit from additional support. Enables data-driven resource allocation in apprenticeship initiatives. Supports evidence-based policy adjustments in youth workforce development. Use Cases: Integration with labor ministry information systems; support for NGO youth programs; academic research on youth employment barriers; corporate social responsibility apprenticeship tracking; municipal youth policy planning. Developed at UFMT (Universidade Federal de Mato Grosso). CAPES/CNPq PTT classification: SKILL (AI-powered computational tool). Part of this content may have been AI-generated under supervision by Daniel Maciel and Arturo Zavala.

Fields of Study & Subjects

AI and HR Technologies Education and Labor Relations Data Mining and Machine Learning Applications

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
11 January 2026
Language
EN