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Applied Sciences· 2026Q2

FairEdu-GCT: A Graph Enhanced, Fairness Aware Framework for Predicting Heterogeneous Returns to Higher Education

Qi’er An, Yanan Jin, Qingyue Wang, Songchao Zhang

Short summary

FairEdu-GCT, a new framework, predicts the full distribution of higher education earnings by integrating institutional relationships and demographic fairness, outperforming baselines by 16.2% in RMSE and 25.1% in PEHE, while reducing demographic parity gaps by 46.5%.

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Field: Computer Science Applications

Computer Science ApplicationsComputer Science