Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants | Paper Citation Record

Observation 214a29b9-6b6a-4755-9dbc-456ec6af08aa · outbound

This paper cites The child opportunity index: improving collaboration between community development and public health.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants The child opportunity index: improving collaboration between community development and public health

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:46.408010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f53b042-31ab-4758-9389-3791fe7e99b6 · outbound

This paper cites A reductions approach to fair classification.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants A reductions approach to fair classification

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:46.455312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb943213-e52e-4f0f-9b30-f705feddc331 · outbound

This paper cites Fair regression: Quantitative definitions and reduction-based algorithms.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Fair regression: Quantitative definitions and reduction-based algorithms

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:46.552557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95feb9ae-787b-49c9-aec9-137324adf5b4 · outbound

This paper cites The social psychology of discrimination: Theory, measurement and consequences.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants The social psychology of discrimination: Theory, measurement and consequences

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:46.601505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef4c1783-d54c-49b5-a3b6-aa19edf596a0 · outbound

This paper cites What makes wrongful discrimination wrong? biases, preferences, stereotypes, and proxies.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants What makes wrongful discrimination wrong? biases, preferences, stereotypes, and proxies

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:46.661670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfa4f4bb-64f0-458e-a071-b05fe23c0912 · outbound

This paper cites The New Jim Crow: Mass Incarceration in the Age of Colorblindness.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants The New Jim Crow: Mass Incarceration in the Age of Colorblindness

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:46.792967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ee68639-41b7-434e-aca0-343b80183185 · outbound

This paper cites Racial/ethnic differences in physician distrust in the United States.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Racial/ethnic differences in physician distrust in the United States

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:46.979440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa9aac9e-accb-4b5a-bbb9-37730755564b · outbound

This paper cites Grades are not normal: Improving exam score models using the logit-normal distribution.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Grades are not normal: Improving exam score models using the logit-normal distribution

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:47.117586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ac59309-06e1-4874-b0e5-b5d46bcf6325 · outbound

This paper cites Rényi fair inference.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Rényi fair inference

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:47.268847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4dc1eb7c-c108-4cec-b0ef-2436b4416f42 · outbound

This paper cites Fairness and Machine Learning: Limitations and Opportunities.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Fairness and Machine Learning: Limitations and Opportunities

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:47.411335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b3cb31a-0aa4-42d2-8eb3-a63b40efa6ca · outbound

This paper cites an unresolved cited work.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Unresolved cited work

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:47.633990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7eabbb0a-c99e-49a5-ac56-c0c697eb8f84 · outbound

This paper cites Inequality and Heterogeneity: A primitive Theory of Social Structure, volume 7.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Inequality and Heterogeneity: A primitive Theory of Social Structure, volume 7

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:47.812407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf2d2c00-0282-4fa9-b78b-ad3bb983329a · outbound

This paper cites Distinction: A Social Critique of the Judgement of Taste.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Distinction: A Social Critique of the Judgement of Taste

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:48.057080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59743022-cedf-4736-8811-fdbf4dae41d3 · outbound

This paper cites The social determinants of health: It's time to consider the causes of the causes.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants The social determinants of health: It's time to consider the causes of the causes

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:48.290766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6069602c-4845-446e-b250-ec504f2ddb4f · outbound

This paper cites Socioeconomic status in health research: One size does not fit all.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Socioeconomic status in health research: One size does not fit all

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:48.452295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a8a9634-10bd-4c13-92fe-f7233a08c1df · outbound

This paper cites Causally interpreting intersectionality theory.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Causally interpreting intersectionality theory

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:48.671036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3b3f296-727f-4ed2-982b-fa005eb1b167 · outbound

This paper cites Building classifiers with independency constraints.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Building classifiers with independency constraints

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:48.806030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5463ebb0-4207-4eb6-97d7-01f746fac145 · outbound

This paper cites Distributional assumptions in educational assessments analysis: Normal distributions versus generalized beta distribution in modeling the phenomenon of learning.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Distributional assumptions in educational assessments analysis: Normal distributions versus generalized beta distribution in modeling the phenomenon of learning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:48.906138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e82ac684-2b48-4aee-985a-8632f544fccf · outbound

This paper cites The effect of environmental regulation on employment in resource-based areas of china—an empirical research based on the mediating effect model.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants The effect of environmental regulation on employment in resource-based areas of china—an empirical research based on the mediating effect model

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:49.060347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb5c16b6-cc4b-4073-9986-ee0c4f316416 · outbound

This paper cites Black Power, volume 48.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Black Power, volume 48

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:49.222221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27e745af-f589-4ddc-8977-8143c021af92 · outbound

This paper cites Fairness in Machine Learning: A Survey.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Fairness in Machine Learning: A Survey

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:49.394617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation acbcc61a-4e0c-4ac8-ae06-133cca93a7c6 · outbound

This paper cites American Community Survey Design and Methodology.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants American Community Survey Design and Methodology

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:49.589466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3d80041-a4c9-4961-bd30-ea4a39d8d8ea · outbound

This paper cites American Community Survey Design and Methodology.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants American Community Survey Design and Methodology

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:49.727814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4d9cd12-ae26-43de-a0cc-c1668e1f51a2 · outbound

This paper cites American Community Survey and Puerto Rico Community Survey Design and Methodology.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants American Community Survey and Puerto Rico Community Survey Design and Methodology

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:49.837615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f0119e6-107e-432b-adee-a1e7222f2084 · outbound

This paper cites 2023 ACS 1-Year PUMS Data Dictionary.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants 2023 ACS 1-Year PUMS Data Dictionary

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:49.989457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7116620f-0433-4c16-80d5-30ce8435cc33 · outbound

This paper cites From race-based to race-conscious medicine: How anti-racist uprisings call us to act.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants From race-based to race-conscious medicine: How anti-racist uprisings call us to act

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:50.161855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98dc0d43-d0cd-4d39-9125-dcf2d7ec1f30 · outbound

This paper cites Changing opportunity: Sociological mechanisms underlying growing class gaps and shrinking race gaps in economic mobility.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Changing opportunity: Sociological mechanisms underlying growing class gaps and shrinking race gaps in economic mobility

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:50.308070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 828c0dee-3f93-4826-9e33-1975a8b6cccd · outbound

This paper cites Path-specific counterfactual fairness.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Path-specific counterfactual fairness

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:50.495446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27f4ef6a-c08c-4432-adff-cc9bf5416cec · outbound

This paper cites Fair prediction with disparate impact: A study of bias in recidivism prediction instruments.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Fair prediction with disparate impact: A study of bias in recidivism prediction instruments

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:50.639975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73eaa4ea-029a-471a-9f15-7f58c9e5a51b · outbound

This paper cites A snapshot of the frontiers of fairness in machine learning.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants A snapshot of the frontiers of fairness in machine learning

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:50.811357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0aba938-1143-497f-8c6d-9526bdc8f423 · outbound

This paper cites Equality of educational opportunity.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Equality of educational opportunity

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:50.941476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6a6eaa0-8bf5-4ed5-9390-1b8543c723c4 · outbound

This paper cites Social capital in the creation of human capital.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Social capital in the creation of human capital

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:51.089005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b9842d8-0e28-43f1-82c4-1e3920056e5e · outbound

This paper cites A spatial analysis of variations in health access: Linking geography, socio-economic status and access perceptions.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants A spatial analysis of variations in health access: Linking geography, socio-economic status and access perceptions

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:51.258697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4be87812-45fa-4870-a8b3-18787cfe655a · outbound

This paper cites Poverty and education.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Poverty and education

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:51.450976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites The Measure and Mismeasure of Fairness.

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 7b61253d-15bd-4a35-a0c2-ccc97e78e20b · outbound

This paper cites Counterfactual risk assessments, evaluation, and fairness.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Counterfactual risk assessments, evaluation, and fairness

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:51.701986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5cd8f87a-6652-4a7b-8d45-2ff95952e05b · outbound

This paper cites Mapping the margins: Intersectionality, identity politics, and violence against women of color.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Mapping the margins: Intersectionality, identity politics, and violence against women of color

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:51.828411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca82a2ab-8480-4fc6-b2b0-d65c3b42c786 · outbound

This paper cites Fairness is not static: Deeper understanding of long term fairness via simulation studies.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Fairness is not static: Deeper understanding of long term fairness via simulation studies

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:52.015937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d90f1b1-a143-4921-8820-ef5625bf6ee7 · outbound

This paper cites Critical Race Theory: An Introduction, volume 87.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Critical Race Theory: An Introduction, volume 87

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:52.158557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 105794bf-3864-4713-8354-bbc2f8f24ff8 · outbound

This paper cites Retiring adult: New datasets for fair machine learning.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Retiring adult: New datasets for fair machine learning

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:52.325286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef2a142e-f523-409f-a78a-593d28527421 · outbound

This paper cites Empirical risk minimization under fairness constraints.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Empirical risk minimization under fairness constraints

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:52.473771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e5570fa-2c4d-442a-81a2-bd5145058a95 · outbound

This paper cites Fairness through awareness.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Fairness through awareness

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:52.603013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4946f7b-7d25-4a7c-900c-627a389691ef · outbound

This paper cites Discrimination and Disrespect.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Discrimination and Disrespect

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:52.775066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d2bb153-082d-493b-a40a-b9ad1c58bd75 · outbound

This paper cites A social vulnerability index for disaster management.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants A social vulnerability index for disaster management

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:52.935395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c35c83d-ea76-4a27-90b7-03f66b836135 · outbound

This paper cites Incorporating area-level social drivers of health in predictive algorithms using electronic health record data.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Incorporating area-level social drivers of health in predictive algorithms using electronic health record data

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:53.057269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c8cd5a7-3bbe-46f4-b0ae-8abb3f5ceb6a · outbound

This paper cites An intersectional definition of fairness.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants An intersectional definition of fairness

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:53.170689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53570fb9-dfbd-42ff-b5f2-1b6f79de9c4b · outbound

This paper cites Structural racism and health inequities: Old issues, new directions.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Structural racism and health inequities: Old issues, new directions

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:53.313366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80eb43a5-3179-406b-ae49-9750357e4a83 · outbound

This paper cites Central Problems in Social Theory: Action, Structure, and Contradiction in Social Analysis.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Central Problems in Social Theory: Action, Structure, and Contradiction in Social Analysis

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:53.441435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fce33dc5-aa04-45c5-a39d-59c4c0007352 · outbound

This paper cites What is Race? Four Philosophical Views.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants What is Race? Four Philosophical Views

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:53.558150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bff16eac-79ac-4c86-9763-b10da5729e44 · outbound

This paper cites Beyond distributive fairness in algorithmic decision making: Feature selection for procedurally fair learning.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Beyond distributive fairness in algorithmic decision making: Feature selection for procedurally fair learning

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:53.746160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a103aee2-277f-4ef6-abe1-aab44605a9bf · outbound

This paper cites Towards a critical race methodology in algorithmic fairness.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Towards a critical race methodology in algorithmic fairness

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:53.901035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 714d3aa8-cd77-4300-a952-76c99448127c · outbound

This paper cites Equality of opportunity in supervised learning.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Equality of opportunity in supervised learning

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:54.027139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7e88d38-d456-4cf8-b2ec-51f8b0e7ceef · outbound

This paper cites Gender and race: (what) are they? (what) do we want them to be? NO \^U S , 34 0 (1): 0 31--55, 2000.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Gender and race: (what) are they? (what) do we want them to be? NO \^U S , 34 0 (1): 0 31--55, 2000

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:54.141238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92e787bd-f1c9-49d4-a9f5-f2513f146648 · outbound

This paper cites Causal Inference: What If.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Causal Inference: What If

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:54.295249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08b6d136-d162-4bd7-b8c7-42453f183563 · outbound

This paper cites Where fairness fails: Data, algorithms, and the limits of antidiscrimination discourse.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Where fairness fails: Data, algorithms, and the limits of antidiscrimination discourse

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:54.453158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ff432fb-c3f3-4eaa-b20d-82c719353248 · outbound

This paper cites Declining job quality in the united states: Explanations and evidence.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Declining job quality in the united states: Explanations and evidence

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:54.595596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67d2da2b-3335-47a0-aba9-ce0d513d204d · outbound

This paper cites What's sex got to do with machine learning? In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, pages 513--513, 2020.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants What's sex got to do with machine learning? In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, pages 513--513, 2020

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:54.726598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bffe4f12-4851-44b6-92c2-2e16f283bb14 · outbound

This paper cites Achieving long-term fairness in sequential decision making.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Achieving long-term fairness in sequential decision making

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:54.865048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 876f2a6d-02e5-4b1e-98c1-73eafa5345c2 · outbound

This paper cites Principal Fairness for Human and Algorithmic Decision-Making.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Principal Fairness for Human and Algorithmic Decision-Making

Reference 59

Resolution: verified exact; local_arxiv, observed 2026-08-05T23:53:04.448540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 20d6f211-f284-4088-9008-26822135b927 · outbound

This paper cites Inequality: A reassessment of the effect of family and schooling in america, 1972.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Inequality: A reassessment of the effect of family and schooling in america, 1972

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:55.208430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b06c7297-fc2b-4e22-a3b2-47f50284c293 · outbound

This paper cites Addressing social vulnerability to hazards.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Addressing social vulnerability to hazards

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:55.379795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6ca4fd5-a5b7-42a3-a35b-11c9b0d7c636 · outbound

This paper cites Quantifying explainable discrimination and removing illegal discrimination in automated decision making.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Quantifying explainable discrimination and removing illegal discrimination in automated decision making

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:55.489142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a58b6acd-4586-4c98-9c77-08f5897cc13a · outbound

This paper cites Algorithmic fairness and structural injustice: Insights from feminist political philosophy.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Algorithmic fairness and structural injustice: Insights from feminist political philosophy

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:55.624496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df6ad956-ace0-41d2-8707-ec7e9d08ceb2 · outbound

This paper cites The use and misuse of counterfactuals in ethical machine learning.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants The use and misuse of counterfactuals in ethical machine learning

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:55.808927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 075ad068-5e17-494b-b19a-07b935b8c343 · outbound

This paper cites The Ethical Algorithm: The Science of Socially Aware Algorithm Design.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants The Ethical Algorithm: The Science of Socially Aware Algorithm Design

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:55.952055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51b9f932-7e36-4593-afde-e520e17d8b77 · outbound

This paper cites Preventing fairness gerrymandering: Auditing and learning for subgroup fairness.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Preventing fairness gerrymandering: Auditing and learning for subgroup fairness

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:56.104589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1d21803-61d0-46f8-97ef-fe2543073516 · outbound

This paper cites Avoiding discrimination through causal reasoning.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Avoiding discrimination through causal reasoning

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:56.260641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7ed25d8-28e5-4f2c-939d-e97325a07552 · outbound

This paper cites Making neighborhood-disadvantage metrics accessible--the neighborhood atlas.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Making neighborhood-disadvantage metrics accessible--the neighborhood atlas

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:56.339568Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56874111-3403-4ebb-898e-2d99a4fb571b · outbound

This paper cites Neighborhood socioeconomic disadvantage and 30-day rehospitalization: A retrospective cohort study.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Neighborhood socioeconomic disadvantage and 30-day rehospitalization: A retrospective cohort study

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:56.473496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23f07a92-df11-456f-9ec4-90a119341a14 · outbound

This paper cites intersectionally fair.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants intersectionally fair

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:56.574127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cdcd6c0b-0818-4ad8-9bee-4b1ea068ac75 · outbound

This paper cites Predicting who reoffends: The neglected role of neighborhood context in recidivism studies.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Predicting who reoffends: The neglected role of neighborhood context in recidivism studies

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:56.676883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9410eb25-91d1-4683-a5d7-2beb9fa34a2d · outbound

This paper cites Counterfactual fairness.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Counterfactual fairness

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:56.774959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64823929-4cad-4eb2-a95a-83401ab31bd3 · outbound

This paper cites The badness of discrimination.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants The badness of discrimination

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:12.081329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0446086c-e9b0-40a8-970b-d040e0136ef0 · outbound

This paper cites Delayed impact of fair machine learning.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Delayed impact of fair machine learning

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:12.067415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9c698361-d306-43f1-bb53-f4270053b0d7 · outbound

This paper cites Causal Reasoning for Algorithmic Fairness.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Causal Reasoning for Algorithmic Fairness

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:57.089236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e752d4d9-a782-4633-b7c9-82354531a4f7 · outbound

This paper cites Neighborhoods, obesity, and diabetes--a randomized social experiment.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Neighborhoods, obesity, and diabetes--a randomized social experiment

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:12.052823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 85316e35-79e1-4498-a326-a061e762cb9e · outbound

This paper cites Survey on Causal-based Machine Learning Fairness Notions.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Survey on Causal-based Machine Learning Fairness Notions

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:57.194673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8104cec1-1012-481b-b4b8-1f220261b72b · outbound

This paper cites Environmental and health impacts of air pollution: A review.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Environmental and health impacts of air pollution: A review

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:12.038127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8e575b13-b325-4d82-ba37-b7e81ef0041d · outbound

This paper cites Social Determinants of Health.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Social Determinants of Health

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:12.023336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f30a8b85-061b-4691-95fc-3ec80487e28c · outbound

This paper cites Fairness-aware learning for continuous attributes and treatments.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Fairness-aware learning for continuous attributes and treatments

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:12.009379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d66dbc3b-3fa8-450d-a4d1-51c23c74d259 · outbound

This paper cites The prodigal paradigm returns: ecology comes back to sociology.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants The prodigal paradigm returns: ecology comes back to sociology

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:11.995472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8675b8d1-f5f0-4431-bffb-97f1ca988083 · outbound

This paper cites A survey on bias and fairness in machine learning.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants A survey on bias and fairness in machine learning

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:11.981269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e93d623a-554e-4802-bf18-7720cc83ecbe · outbound

This paper cites Fairness in risk assessment instruments: Post-processing to achieve counterfactual equalized odds.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Fairness in risk assessment instruments: Post-processing to achieve counterfactual equalized odds

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:11.967552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2c79dba9-d0f0-432e-affc-103c0de127ee · outbound

This paper cites Prediction-Based Decisions and Fairness: A Catalogue of Choices, Assumptions, and Definitions.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Prediction-Based Decisions and Fairness: A Catalogue of Choices, Assumptions, and Definitions

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:57.733679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 833c5d09-f8db-4d74-b86d-83c0d199bea3 · outbound

This paper cites Equality and discrimination.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Equality and discrimination

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:11.952634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4d0ce895-2c37-42e6-a0af-3c3754109e87 · outbound

This paper cites Fair inference on outcomes.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Fair inference on outcomes

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:11.938374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation df9147cb-cfc5-4eb9-902c-63c178f7eea8 · outbound

This paper cites Learning optimal fair policies.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Learning optimal fair policies

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:11.924635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 92e94489-361e-4b4b-9e21-5cef5c8ce558 · outbound

This paper cites Optimal training of fair predictive models.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Optimal training of fair predictive models

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:11.910470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fc27f726-ccdc-4a80-a652-41ba0c8b37d2 · outbound

This paper cites Translation tutorial: 21 fairness definitions and their politics.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Translation tutorial: 21 fairness definitions and their politics

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:11.895804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 797af294-d12f-433f-a689-595171e9dfa7 · outbound

This paper cites Causal conceptions of fairness and their consequences.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Causal conceptions of fairness and their consequences

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:11.879824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ad80f90d-ac17-4b02-90e2-8585ecfafefc · outbound

This paper cites Dissecting racial bias in an algorithm used to manage the health of populations.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Dissecting racial bias in an algorithm used to manage the health of populations

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:11.865719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c0c7c8d7-a204-4d35-a66a-df925c19e13c · outbound

This paper cites Structural racism: A 60-year-old black woman with breast cancer.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Structural racism: A 60-year-old black woman with breast cancer

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:11.851632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f0262a5b-f126-43f3-8d31-64d6a661f374 · outbound

This paper cites Causality.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Causality

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:11.837616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 59cbd7c4-96ad-41e7-ae2b-607e0ec172b4 · outbound

This paper cites A review on fairness in machine learning.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants A review on fairness in machine learning

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:11.823811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 51875cfe-a80d-460d-9706-50730bad6d78 · outbound

This paper cites Elements of Causal Inference: Foundations and Learning Algorithms.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Elements of Causal Inference: Foundations and Learning Algorithms

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-05T23:52:58.610079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 323a021f-c8d7-4435-bc02-de638bc5d5b3 · outbound

This paper cites Legislating against discrimination: An international survey of anti-discrimination norms.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Legislating against discrimination: An international survey of anti-discrimination norms

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:11.799849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 71964918-c54e-45b2-b69b-1a23f694ddab · outbound

This paper cites Structural Injustice: Power, Advantage, and Human Rights.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Structural Injustice: Power, Advantage, and Human Rights

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:11.785815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 30db1368-65f6-40d7-b613-2fc23adf6249 · outbound

This paper cites Environmental regulation and employment in resource-based cities in china: The threshold effect of industrial structure transformation.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Environmental regulation and employment in resource-based cities in china: The threshold effect of industrial structure transformation

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:11.771907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c211e41c-e775-453e-9357-aedad66644ab · outbound

This paper cites A Theory of Justice.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants A Theory of Justice

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:11.758091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 43c56d55-6690-4d53-aceb-5fdd8f1b56ce · outbound

This paper cites Justice as Fairness: A Restatement.

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants Justice as Fairness: A Restatement

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T23:53:11.744583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers