Paper Citation Record · LEDGER

A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:1901.10002.

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

pith.paper-citation-record.v1
1901.10002 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:36:02.516620Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-10T06:15:00.866473Z

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 e0604930-6a62-49a9-aa62-cd079a2a662b · inbound

Navigating the Risks: A Survey of Security, Privacy, and Ethics Threats in LLM-Based Agents cites this paper.

Navigating the Risks: A Survey of Security, Privacy, and Ethics Threats in LLM-Based Agents A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle

Reference 248

Resolution: unresolved; no resolver link, observed 2026-08-12T20:36:02.516620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0e57550-c6fb-4a94-bcd2-02a45bc245cf · inbound

Using Machine Bias To Measure Human Bias cites this paper.

Using Machine Bias To Measure Human Bias A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-12T11:34:37.872738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdbbc966-5c57-4b59-9187-a136c54ac028 · inbound

Generative AI regulation can learn from social media regulation cites this paper.

Generative AI regulation can learn from social media regulation A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T15:04:59.640292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 414bb3b2-7627-464f-8a2a-3a80dab0ef67 · inbound

ALBAR: Adversarial Learning approach to mitigate Biases in Action Recognition cites this paper.

ALBAR: Adversarial Learning approach to mitigate Biases in Action Recognition A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-09T20:04:48.491147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83934fcf-303f-43bd-9b8f-921b07351db3 · inbound

Perception-Driven Bias Detection in Machine Learning via Crowdsourced Visual Judgment cites this paper.

Perception-Driven Bias Detection in Machine Learning via Crowdsourced Visual Judgment A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T15:15:26.000405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89bf0bca-b068-492d-8c87-dd23b5ba7e33 · inbound

A Cross-Cultural Comparison of LLM-based Public Opinion Simulation: Evaluating Chinese and U.S. Models on Diverse Societies cites this paper.

A Cross-Cultural Comparison of LLM-based Public Opinion Simulation: Evaluating Chinese and U.S. Models on Diverse Societies A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:33.214477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c174d57e-61da-4297-825c-95b42f5741f5 · inbound

Causal inference for social network formation cites this paper.

Causal inference for social network formation A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle

Reference 182

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:11:04.074997Z

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 2ec56b60-8e5b-49fd-88e3-82c1f6657482 · inbound

Toward Calibrated, Fair, and accurate Deepfake Detection cites this paper.

Toward Calibrated, Fair, and accurate Deepfake Detection A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle

Reference 200

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T07:11:45.026905Z

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 9e41c181-396d-4f6e-a9e1-25c76c3289b1 · inbound

The Khipu Problem: Institutional Legibility Under Distributed Cognition cites this paper.

The Khipu Problem: Institutional Legibility Under Distributed Cognition A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:25:45.047005Z

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 4ee406c0-f793-4297-b331-4cf16302a1e4 · inbound

Sources of Inequity and Fairness Risks in Wellbeing Sensing cites this paper.

Sources of Inequity and Fairness Risks in Wellbeing Sensing A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-01T07:13:14.688466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.