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Authors
Kuznetsov, Oleksandr https://orcid.org/0000-0003-2331-6326
Melchiori, Michele https://orcid.org/0009-0009-6332-0435
Galdelli, Alessandro https://orcid.org/0000-0002-4140-6424
Frontoni, Emanuele https://orcid.org/0000-0002-8893-9244
Arnesano, Marco https://orcid.org/0000-0003-1700-3075
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Article History
Received: 9 October 2025
Accepted: 9 February 2026
First Online: 25 February 2026
Declarations
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: This research was conducted in accordance with European data protection regulations and ethical guidelines for AI systems in social applications. All synthetic data generation procedures were designed to prevent potential harm to individuals with disabilities. The federated learning framework preserves data locality and individual privacy while enabling collaborative improvement of employment services.
: The authors declare no competing financial or non-financial interests related to this research. The author Alessandro Galdelli is a member of the Editorial board of this journal.
