Paper Citation Record · LEDGER

The Measure and Mismeasure of Fairness

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:1808.00023.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1808.00023 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T13:35:49.282410Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-04T09:59:45.885102Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 7150da02-0317-40d4-a5dc-9b3e098d9455 · inbound

Fairness criteria through the lens of directed acyclic graphical models cites this paper.

Fairness criteria through the lens of directed acyclic graphical models The Measure and Mismeasure of Fairness

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-25T14:50:57.025586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 28343d85-b347-408b-98a6-f9c0fca453ce · inbound

A Causal Bayesian Networks Viewpoint on Fairness cites this paper.

A Causal Bayesian Networks Viewpoint on Fairness The Measure and Mismeasure of Fairness

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-05-24T21:34:58.740920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e8c33288-adad-46b0-b23e-74fbc9f0f1db · inbound

Aligning AI With Shared Human Values cites this paper.

Aligning AI With Shared Human Values The Measure and Mismeasure of Fairness

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-05-21T14:41:26.523945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c1f51517-f751-499f-a912-744a514ef5b4 · inbound

Critical Appraisal of Fairness Metrics in Clinical Predictive AI cites this paper.

Critical Appraisal of Fairness Metrics in Clinical Predictive AI The Measure and Mismeasure of Fairness

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T23:35:03.105328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1cf2fb1b-e67a-4faa-b778-6dfefd5081c3 · inbound

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants cites this paper.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants The Measure and Mismeasure of Fairness

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:51.587809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cb17d54-adb6-40d5-b728-0f464019898c · inbound

Private, Verifiable, and Auditable AI Systems cites this paper.

Private, Verifiable, and Auditable AI Systems The Measure and Mismeasure of Fairness

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-05T15:43:58.854135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7cd4455-fd2b-40ac-8b51-fae5f198df1e · inbound

Trustworthy AI Suffers from Invariance Conflicts and Causality is The Solution cites this paper.

Trustworthy AI Suffers from Invariance Conflicts and Causality is The Solution The Measure and Mismeasure of Fairness

Reference 281

Resolution: metadata mismatch; arxiv_id, observed 2026-05-09T05:45:21.117630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ff5d4b88-a6d0-457f-8118-bed753e8a161 · inbound

Triage Score: A Counterfactual Risk Assessment Instrument cites this paper.

Triage Score: A Counterfactual Risk Assessment Instrument The Measure and Mismeasure of Fairness

Reference 42

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T07:39:39.119527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2bebd3af-68c7-4277-ba40-0cf4f21e07b5 · inbound

Unmasking LAION-5B: Age, Gender, Race, and Emotion Biases in Large-Scale Image Datasets cites this paper.

Unmasking LAION-5B: Age, Gender, Race, and Emotion Biases in Large-Scale Image Datasets The Measure and Mismeasure of Fairness

Reference 82

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T09:59:45.886451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9c45ce76-fb8d-4d0a-a4a3-111756a6573d · inbound

OT-FairBoost: Optimal Transport-Guided Gradient Boosting for Fairness Regularization on Tabular Data cites this paper.

OT-FairBoost: Optimal Transport-Guided Gradient Boosting for Fairness Regularization on Tabular Data The Measure and Mismeasure of Fairness

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-07-31T20:25:01.991334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0330e780-5955-4dfa-a772-4099dcae066f · inbound

Negotiating Risk Boundaries in AI for Policing Through Mixed-Stakeholder Deliberation cites this paper.

Negotiating Risk Boundaries in AI for Policing Through Mixed-Stakeholder Deliberation The Measure and Mismeasure of Fairness

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-08T13:35:49.282410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.