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4,299,418 works, Canadian by any of four routes.

Every filter state is a URL; the URL is the query; the query is citable via /q/⟨hash⟩. The page, the API and the export parse the same parameters.

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The current cohort, streamed from the database: every work column, the machine labels, the provisional scores, and the per-row validation status. Exports are capped at 100,000 rows. Mints a permanent /q/ link for this exact query. The same filters always produce the same link, whoever asks.

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Proceedings of the AAAI/ACM Conference on AI Ethics and Society
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Direct Codex and Gemma labels are unvalidated and sparse. Distilled predictions cover the full frame and are also unvalidated. Choose the evidence source explicitly; absence of a direct label is never a negative label.

affaffiliation
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The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

40 results · 1 filter active ·
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20202025
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Machine labels · sparse coverage
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
40 works in the cohort · of 4,299,418page 1 of 1

Labels cover 0 of 40 works in this cohort. The rest are unlabeled, which is not a negative label: the label table is sparse today and grows as labeling rounds land.

Distilled predictions cover 40 of 40 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affunlabeled
Responsible Reporting for Frontier AI Development
Noam Kolt, Markus Anderljung, Joslyn Barnhart, Asher Brass, Kevin M. Esvelt, Gillian K. Hadfield +4 more
2024· article· en· Proceedings of the AAAI/ACM Conference on AI Ethics and Society· Business, Management and Accounting
distilled prediction:candidate · noneconsensus · none
6
citations
affunlabeled
Co-Producing AI: Toward an Augmented, Participatory Lifecycle
Rashid Mushkani, Hugo Berard, Toumadher Ammar, Cassandre Chatonnier, Shin Alexandre Koseki
2025· article· en· Proceedings of the AAAI/ACM Conference on AI Ethics and Society· Business, Management and Accounting
distilled prediction:candidate · noneconsensus · none
4
citations
fundno affunlabeled
Algorithmic Fairness from a Non-ideal Perspective
Sina Fazelpour, Zachary C. Lipton
2020· preprint· en· Proceedings of the AAAI/ACM Conference on AI Ethics and Society· Social Sciences
distilled prediction:candidate · metaepi_narrow+sts+scholarly_communication+research_integrityconsensus · research_integrity
2
citations
afffundunlabeled
A Principled Approach for Data Bias Mitigation
Bruno Scarone, Alfredo Viola, Renée J. Miller, Ricardo Baeza‐Yates
2025· article· en· Proceedings of the AAAI/ACM Conference on AI Ethics and Society· Decision Sciences
distilled prediction:candidate · metaresearchconsensus · none
2
citations
affunlabeled
Model Multiplicity for Responsible AI
Prakhar Ganesh
2025· article· en· Proceedings of the AAAI/ACM Conference on AI Ethics and Society· Engineering
distilled prediction:candidate · noneconsensus · none
0
citations
afffundunlabeled
Fairness in Federated Learning: Fairness for Whom?
Afaf Taïk, Khaoula Chehbouni, Golnoosh Farnadi
2025· article· en· Proceedings of the AAAI/ACM Conference on AI Ethics and Society· Social Sciences
distilled prediction:candidate · stsconsensus · none
0
citations
afffundunlabeled
What’s Individual About Individual Fairness?
Shai Ben-David, Pascale Gourdeau, Tosca Lechner, Ruth Urner
2025· article· en· Proceedings of the AAAI/ACM Conference on AI Ethics and Society· Social Sciences
distilled prediction:candidate · sts+research_integrityconsensus · none
0
citations
affunlabeled
Data Cleaning, Discard Studies, and Discretionary Power
Pınar Barlas
2025· article· en· Proceedings of the AAAI/ACM Conference on AI Ethics and Society· Computer Science
distilled prediction:candidate · metaresearch+open_scienceconsensus · open_science
0
citations
affunlabeled
Incident Analysis for AI Agents
Carson Ezell, Xavier Roberts-Gaal, Alan Chan
2025· article· en· Proceedings of the AAAI/ACM Conference on AI Ethics and Society· Computer Science
distilled prediction:candidate · noneconsensus · none
0
citations

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