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Evidence record 18294 · automatically gathered

Fairness in Link Prediction Beyond Demographic Parity: A Reproducibility Study

In fair ranked link prediction, demographic parity ($Δ_\mathrm{DP}$) is a common fairness metric. Yet, Mattos et al. (2025) argue that it fails to detect exposure bias because it ignores where links appear in the ranking. In this study, we reproduce this claim by showing that $Δ_\mathrm{DP}$ can indicate aggregate parity even when some subgroup-pair links are systematically ranked lower than others. The proposed rank-aware Normalized Discounted KL-divergence (NDKL), however, does detect such dis

Record details

Published: 10 August 2026
Source: arXiv fairness query
Category: Research
Topics: Bias & fairness
Retrieved: 11 August 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

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How to cite this record

ethics.ai (10 August 2026), “Fairness in Link Prediction Beyond Demographic Parity: A Reproducibility Study,” evidence record 18294, https://ethics.ai/record/18294 (originally published by arXiv fairness query).

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