Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-10T01:35:33.964568Z
Paper Citation Record · LEDGER
Fairness Audits of Institutional Risk Models in Deployed ML Pipelines
As of 12 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2604.19468.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
13 of 13 outbound references displayed
- verified exact4
- verified fuzzy2
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch7
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation a50c0414-1ad3-4ed9-a3c4-895e178045bb · outbound
This paper cites Risk, Retention, and the Algorithmic Institu- tion: Artificial Intelligence as a Policy Response to Higher Education in Crisis.
Fairness Audits of Institutional Risk Models in Deployed ML Pipelines Risk, Retention, and the Algorithmic Institu- tion: Artificial Intelligence as a Policy Response to Higher Education in Crisis
Reference 1
- Resolution
- verified exact
- doi, observed 2026-05-10T01:35:54.574071Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 874e4246-f81f-4b7e-9431-b941852fbd68 · outbound
This paper cites “This Is Not a Data Problem.
Fairness Audits of Institutional Risk Models in Deployed ML Pipelines “This Is Not a Data Problem
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T09:17:48.326831Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation f6f162fb-f8d4-4822-a7ff-e0b751417936 · outbound
This paper cites Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency , location =.
Fairness Audits of Institutional Risk Models in Deployed ML Pipelines Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency , location =
Reference 3
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T01:35:54.581430Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation e1a82870-36cd-495d-964e-371de35db6ea · outbound
This paper cites A Framework of High-Stakes Algorithmic Decision-Making for the Public Sector Developed through a Case Study of Child- Welfare.
Fairness Audits of Institutional Risk Models in Deployed ML Pipelines A Framework of High-Stakes Algorithmic Decision-Making for the Public Sector Developed through a Case Study of Child- Welfare
Reference 4
- Resolution
- verified exact
- doi, observed 2026-05-10T01:35:54.572385Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 514951ed-8b44-4ac5-a015-30362c1e5649 · outbound
This paper cites InProceedings of the CHI Conference on Human Factors in Computing Systems.
Fairness Audits of Institutional Risk Models in Deployed ML Pipelines InProceedings of the CHI Conference on Human Factors in Computing Systems
Reference 5
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T01:35:54.576684Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation b2b5c99b-a06d-44bb-8684-ac2f692b9b23 · outbound
This paper cites They Shall Be Fair, Transparent, and Robust: Auditing Learning Analytics Systems.
Fairness Audits of Institutional Risk Models in Deployed ML Pipelines They Shall Be Fair, Transparent, and Robust: Auditing Learning Analytics Systems
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T09:17:48.330868Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 39bf9177-1815-4b25-a8f4-68dce50e8bbf · outbound
This paper cites Science , author =.
Fairness Audits of Institutional Risk Models in Deployed ML Pipelines Science , author =
Reference 7
- Resolution
- metadata mismatch
- doi, observed 2026-05-10T01:35:54.578439Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 47b5e00c-9b86-4262-8c7e-28ce14efe777 · outbound
This paper cites Proceedings of the Conference on Fairness, Accountability, and Transparency , pages =.
Fairness Audits of Institutional Risk Models in Deployed ML Pipelines Proceedings of the Conference on Fairness, Accountability, and Transparency , pages =
Reference 8
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T01:35:54.570474Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation b79b9a23-65bd-4242-83e3-c368d07aa88d · outbound
This paper cites Jacobs and Hanna Wallach.
Fairness Audits of Institutional Risk Models in Deployed ML Pipelines Jacobs and Hanna Wallach
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T01:35:54.589607Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation dfa7d732-df34-4579-bb0f-a08667c41adc · outbound
This paper cites Difficult Lessons on Social Prediction from Wisconsin Public Schools.
Fairness Audits of Institutional Risk Models in Deployed ML Pipelines Difficult Lessons on Social Prediction from Wisconsin Public Schools
Reference 10
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T13:31:03.298936Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation ed638369-eb94-42a1-a10c-955af8a0b0df · outbound
This paper cites A Human-Centered Review of Algorithms in Decision-MakinginHigherEducation.
Fairness Audits of Institutional Risk Models in Deployed ML Pipelines A Human-Centered Review of Algorithms in Decision-MakinginHigherEducation
Reference 11
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T01:35:54.584530Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation aacdd2cb-1843-43f3-9318-1d10f83da321 · outbound
This paper cites Balancing Fairness: Unveiling the Potential of SMOTE-Driven Oversampling in AI Model Enhancement.
Fairness Audits of Institutional Risk Models in Deployed ML Pipelines Balancing Fairness: Unveiling the Potential of SMOTE-Driven Oversampling in AI Model Enhancement
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T01:35:54.587230Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 0ef9423d-faf9-48e5-aee1-d2f112ba3e3b · outbound
This paper cites In: Proceedings of the 3rd Innovations in Theoretica l Computer Science Conference On - ITCS ’12, pp.
Fairness Audits of Institutional Risk Models in Deployed ML Pipelines In: Proceedings of the 3rd Innovations in Theoretica l Computer Science Conference On - ITCS ’12, pp
Reference 13
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T01:35:54.592385Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Pith citing papers
No inbound Pith citation observations are available.