Paper Citation Record · LEDGER

Whose fairness? Structural concentration in AI bias research

As of 10 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2607.05574.

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

pith.paper-citation-record.v1
2607.05574 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T05:35:55.246993Z

measured 32 of 32 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

32 of 32 outbound references displayed

verified exact11
verified fuzzy0
unresolved17
parse uncertain0
malformed identifier4
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0db5c404-9248-480d-b79f-a481d2ff159e · outbound

This paper cites Microchemical Journal205, 111307 (2024) https://doi.org/10.1016/j.microc.2024.111307.

Whose fairness? Structural concentration in AI bias research Microchemical Journal205, 111307 (2024) https://doi.org/10.1016/j.microc.2024.111307

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-11T05:37:48.329549Z

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 21b023cb-205a-4572-90eb-5e34f53039a1 · outbound

This paper cites Drug Discovery Today29(6), 103992 (2024) https://doi.org/10.1016/j.

Whose fairness? Structural concentration in AI bias research Drug Discovery Today29(6), 103992 (2024) https://doi.org/10.1016/j

Reference 2

Resolution: malformed identifier; no resolver link, observed 2026-07-11T05:35:55.246993Z

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Observation 2e3b8174-a6f9-4ac3-9dbd-82cf3fadf156 · outbound

This paper cites Science Advances4(1), 5580 (2018) https://doi.org/10.1126/sciadv.aao5580 16.

Whose fairness? Structural concentration in AI bias research Science Advances4(1), 5580 (2018) https://doi.org/10.1126/sciadv.aao5580 16

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-11T05:35:55.246993Z

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Observation 7fa5e5c8-8fce-447a-9290-5a8a20b7f1ff · outbound

This paper cites Sci6(1), 3 (2023) https://doi.org/10.3390/ sci6010003.

Whose fairness? Structural concentration in AI bias research Sci6(1), 3 (2023) https://doi.org/10.3390/ sci6010003

Reference 4

Resolution: malformed identifier; no resolver link, observed 2026-07-11T05:35:55.246993Z

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Observation fcd963a1-39cc-43a9-9544-0b3c56b27736 · outbound

This paper cites WIREs Data Mining and Knowledge Discovery10(3), 1356 (2020) https://doi.org/10.1002/widm.1356.

Whose fairness? Structural concentration in AI bias research WIREs Data Mining and Knowledge Discovery10(3), 1356 (2020) https://doi.org/10.1002/widm.1356

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-11T05:35:55.246993Z

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Observation f630302e-928e-47a8-846b-610d1b8dd41b · outbound

This paper cites IEEE Trans- actions on Neural Networks and Learning Systems35(1), 117–131 (2024) https: //doi.org/10.1109/TNNLS.2022.3172365.

Whose fairness? Structural concentration in AI bias research IEEE Trans- actions on Neural Networks and Learning Systems35(1), 117–131 (2024) https: //doi.org/10.1109/TNNLS.2022.3172365

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-07-11T05:37:48.395061Z

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 a28394d1-9104-448e-96f5-e6f97a17fc2c · outbound

This paper cites The Lancet Digital Health6(1), 12–22 (2024) https://doi.org/10.1016/S2589-7500(23)00225-X.

Whose fairness? Structural concentration in AI bias research The Lancet Digital Health6(1), 12–22 (2024) https://doi.org/10.1016/S2589-7500(23)00225-X

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-11T05:35:55.246993Z

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Observation ef9ece3f-d60d-479e-9935-1e719246f503 · outbound

This paper cites Association for Computational Linguistics, Abu Dhabi, UAE (2025).

Whose fairness? Structural concentration in AI bias research Association for Computational Linguistics, Abu Dhabi, UAE (2025)

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-11T05:35:55.246993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdafa8e3-ca5c-4ac4-a19d-67ce59682f48 · outbound

This paper cites https://arxiv.org/abs/2603.07792.

Whose fairness? Structural concentration in AI bias research https://arxiv.org/abs/2603.07792

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-07-11T05:37:50.082762Z

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 15428930-510b-4180-9d08-b134c4ac1c63 · outbound

This paper cites Artificial Intelligence and Law (2024) https://doi.org/10.1007/s10506-024-09389-8.

Whose fairness? Structural concentration in AI bias research Artificial Intelligence and Law (2024) https://doi.org/10.1007/s10506-024-09389-8

Reference 10

Resolution: verified exact; doi, observed 2026-07-11T05:37:48.378243Z

Source-reported events for the cited work

correction dated 2024-04-02. Source: crossref record 10.1007/s10506-024-09400-2->10.1007/s10506-024-09389-8:correction, observed 2026-07-11T02:59:00.047963+00:00. This notice travels one citation hop only.

correction dated 2026-04-10. Source: crossref record 10.1007/s10506-026-09514-9->10.1007/s10506-024-09389-8:correction, observed 2026-07-11T03:02:07.093365+00:00. This notice travels one citation hop only.

Observation 480febb7-e0a3-4aa5-8eae-8f4a75c47293 · outbound

This paper cites In: Proceedings of the Conference on Fairness, Accountability, and Transparency.

Whose fairness? Structural concentration in AI bias research In: Proceedings of the Conference on Fairness, Accountability, and Transparency

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-11T05:35:55.246993Z

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Observation 87892ee7-f6ba-47d9-8ebd-eb223537a89c · outbound

This paper cites ACM Computing Surveys54(6), 1–35 (2021) https://doi.org/10.1145/3457607.

Whose fairness? Structural concentration in AI bias research ACM Computing Surveys54(6), 1–35 (2021) https://doi.org/10.1145/3457607

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-11T05:35:55.246993Z

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Observation aaab325a-42c7-4318-b007-a403144ffccd · outbound

This paper cites ACM Computing 17 Surveys56(7), 1–38 (2024) https://doi.org/10.1145/3616865.

Whose fairness? Structural concentration in AI bias research ACM Computing 17 Surveys56(7), 1–38 (2024) https://doi.org/10.1145/3616865

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-11T05:35:55.246993Z

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Observation 7a5a46b8-841b-4b0a-8265-745f39f0ec3b · outbound

This paper cites ACM Journal on Responsible Computing1(2), 1–52 (2024) https://doi.org/10.1145/3631326.

Whose fairness? Structural concentration in AI bias research ACM Journal on Responsible Computing1(2), 1–52 (2024) https://doi.org/10.1145/3631326

Reference 14

Resolution: verified exact; doi, observed 2026-07-11T05:37:48.407887Z

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 269ce902-6310-498b-a698-b3c7a3cebb64 · outbound

This paper cites ACM Comput.

Whose fairness? Structural concentration in AI bias research ACM Comput

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-11T05:35:55.246993Z

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Observation 0cc919e7-edbd-471b-98df-a2deb24bb151 · outbound

This paper cites ACM Computing Surveys55(13s), 1–37 (2023) https://doi.org/10.1145/3597199.

Whose fairness? Structural concentration in AI bias research ACM Computing Surveys55(13s), 1–37 (2023) https://doi.org/10.1145/3597199

Reference 16

Resolution: verified exact; doi, observed 2026-07-11T05:37:48.356892Z

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 56c1ddf4-5dca-42d6-889e-69d9335f1246 · outbound

This paper cites A Survey on Fairness in Large Language Models.

Whose fairness? Structural concentration in AI bias research A Survey on Fairness in Large Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-11T05:35:55.246993Z

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Observation 23ad11ea-3e8b-46de-aaac-82c85067ea38 · outbound

This paper cites Computational Linguistics50(3), 1097–1179 (2024) https://doi.org/10.

Whose fairness? Structural concentration in AI bias research Computational Linguistics50(3), 1097–1179 (2024) https://doi.org/10

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-11T05:35:55.246993Z

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Observation 83e6d2e6-ac80-4269-83bf-64194dd53ee7 · outbound

This paper cites ACM SIGKDD Explorations Newsletter26(1), 34–48 (2024) https://doi.

Whose fairness? Structural concentration in AI bias research ACM SIGKDD Explorations Newsletter26(1), 34–48 (2024) https://doi

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-11T05:35:55.246993Z

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Observation 6301114c-0d5b-4c78-8063-ecc77d88883e · outbound

This paper cites In: Proceedings of the 30th International Conference on Intelligent User Interfaces, pp.

Whose fairness? Structural concentration in AI bias research In: Proceedings of the 30th International Conference on Intelligent User Interfaces, pp

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-11T05:35:55.246993Z

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Observation f39e21b6-cd87-47c1-94d1-d9cfb774526f · outbound

This paper cites Journal of Nonverbal Behavior48(2), 323– 344 (2024) https://doi.org/10.1007/s10919-024-00454-z.

Whose fairness? Structural concentration in AI bias research Journal of Nonverbal Behavior48(2), 323– 344 (2024) https://doi.org/10.1007/s10919-024-00454-z

Reference 21

Resolution: verified exact; doi, observed 2026-07-11T05:37:48.361853Z

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

Observation b2c68bc5-02a2-4712-81e7-d3a226780268 · outbound

This paper cites PLOS ONE10(2), 1–15 (2015) https://doi.org/10.1371/journal.

Whose fairness? Structural concentration in AI bias research PLOS ONE10(2), 1–15 (2015) https://doi.org/10.1371/journal

Reference 22

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Observation a3bc900f-3dce-49cf-b323-bea72573eb10 · outbound

This paper cites The Limits of Global Inclusion in AI Development.

Whose fairness? Structural concentration in AI bias research The Limits of Global Inclusion in AI Development

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-11T05:35:55.246993Z

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Observation 42be1f2e-6e91-4c9a-a336-f52359fbe750 · outbound

This paper cites an unresolved cited work.

Whose fairness? Structural concentration in AI bias research Unresolved cited work

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-07-11T05:37:48.372404Z

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 fd1d8580-981e-432b-9289-e48d121b7611 · outbound

This paper cites Science 159(3810), 56–63 (1968) https://doi.org/10.1126/science.159.3810.56 https://www.science.org/doi/pdf/10.1126/science.159.3810.56.

Whose fairness? Structural concentration in AI bias research Science 159(3810), 56–63 (1968) https://doi.org/10.1126/science.159.3810.56 https://www.science.org/doi/pdf/10.1126/science.159.3810.56

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-11T05:35:55.246993Z

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Observation 587630ee-bdbe-4b7e-9324-f10d2163e4dd · outbound

This paper cites Nature Communications 15(1), 7527 (2024) https://doi.org/10.1038/s41467-024-51714-x.

Whose fairness? Structural concentration in AI bias research Nature Communications 15(1), 7527 (2024) https://doi.org/10.1038/s41467-024-51714-x

Reference 26

Resolution: verified exact; doi, observed 2026-07-11T05:37:48.399581Z

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

Observation 60fc1400-1a7b-46d0-bb85-167bede0a173 · outbound

This paper cites PLOS Global Public Health4(1), 0002513 (2024) https://doi.org/10.1371/journal.pgph.0002513.

Whose fairness? Structural concentration in AI bias research PLOS Global Public Health4(1), 0002513 (2024) https://doi.org/10.1371/journal.pgph.0002513

Reference 27

Resolution: verified exact; doi, observed 2026-07-11T05:37:48.340338Z

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

Observation be308e57-ae55-4f7e-b3c8-c05f883df3a2 · outbound

This paper cites Science366(6464), 447–453 (2019) https://doi.org/10.1126/science.aax2342.

Whose fairness? Structural concentration in AI bias research Science366(6464), 447–453 (2019) https://doi.org/10.1126/science.aax2342

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-11T05:35:55.246993Z

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Observation ad449a90-76a1-466a-85ea-b42b291bc0c0 · outbound

This paper cites FAccT ’21, pp.

Whose fairness? Structural concentration in AI bias research FAccT ’21, pp

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-11T05:35:55.246993Z

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Observation 5f770ae9-d04d-4948-abf2-3f3a41a41414 · outbound

This paper cites In: Proceedings of the 3rd Innovations in Theoretical Computer Sci- ence Conference.

Whose fairness? Structural concentration in AI bias research In: Proceedings of the 3rd Innovations in Theoretical Computer Sci- ence Conference

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-11T05:35:55.246993Z

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Observation aa7406d8-afaa-4e95-9bea-e4a43876db63 · outbound

This paper cites Cambridge University Press, Cambridge (2023).

Whose fairness? Structural concentration in AI bias research Cambridge University Press, Cambridge (2023)

Reference 31

Resolution: verified exact; doi, observed 2026-07-11T05:37:48.394636Z

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 f540a5ca-76f5-4b3e-8ca0-d3225478dbee · outbound

This paper cites 1: Domain distribution and temporal dynamics.(a)Distribution of 692 papers across five thematic domains.(b)Annual publication volume by domain (2015–2026).

Whose fairness? Structural concentration in AI bias research 1: Domain distribution and temporal dynamics.(a)Distribution of 692 papers across five thematic domains.(b)Annual publication volume by domain (2015–2026)

Reference 32

Resolution: malformed identifier; no resolver link, observed 2026-07-11T05:35:55.246993Z

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Pith citing papers

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