SIGMOD 2020 Tutorial on Fairness and Bias in Peer Review and other Sociotechnical Intelligent Systems
Summary: SIGMOD 2020 tutorial on fairness and bias at the data-management–sociotechnical interface, defining fairness via protected characteristics and surveying auditing methods. It highlights bias in peer review and distributed evaluations and examines how data collection shapes outcomes. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Nihar B. Shah
- 2. Zachary Lipton
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,892 | Identifying Insufficient Data Coverage for Ordinal Continuous-Valued Attributes | 2021 | SIGMOD | 4.8925683e-05 |
| 9,712 | Maximizing Fair Content Spread via Edge Suggestion in Social Networks | 2022 | VLDB | 4.299267e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 0 of 0 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
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