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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.

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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Ethics and Social Impacts of AI
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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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venuejournal
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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.

1,449 results · 1 filter active ·
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20002025
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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.
1,449 works in the cohort · of 4,299,418page 7 of 29

Labels cover 12 of 1,449 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 1,449 of 1,449 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affunlabeled
Data science meets law
Shlomi Hod, Karni Chagal-Feferkorn, Niva Elkin-Koren, Avigdor Gal
2022· article· en· Communications of the ACM· Social Sciences
distilled prediction:candidate · metaresearch+sts+open_scienceconsensus · sts+open_science
11
citations
venueno affunlabeled
Human Where?
Marc A. Anderson, Karën Fort
2022· article· en· The International Review of Information Ethics· Social Sciences
distilled prediction:candidate · insufficient_payloadconsensus · none
11
citations
affunlabeled
Nothing Is Harder to Resist Than the Temptation of AI
Andrew Park, Jan Kietzmann, Jayson Killoran, Yuanyuan Cui, Patrick van Esch, Amir Dabirian
2023· article· en· IT Professional· Social Sciences
distilled prediction:candidate · noneconsensus · none
11
citations
aboutno affunlabeled
AI as a Legal Person
Migle Laukyte
2019· article· en· Social Sciences
distilled prediction:candidate · insufficient_payloadconsensus · insufficient_payload
10
citations
aboutno affunlabeled
Should algorithms be regulated by government?
Robert Smith, Pierre Desrochers
2020· article· en· Canadian Public Administration· Social Sciences
distilled prediction:candidate · noneconsensus · none
10
citations
affno abstractunlabeled
The science fiction science method
Iyad Rahwan, Azim Shariff, Jean‐François Bonnefon
2025· review· en· Nature· Social Sciences
distilled prediction:candidate · metaresearch+sts+scholarly_communication+research_integrityconsensus · sts+research_integrity
9
citations
affno abstractunlabeled
The impact of advanced AI systems on democracy
Christopher Summerfield, Lisa P. Argyle, Michiel A. Bakker, Teddy Collins, Esin Durmus, Tyna Eloundou +17 more
2025· review· en· Nature Human Behaviour· Social Sciences
distilled prediction:candidate · sts+research_integrityconsensus · research_integrity
9
citations
affunlabeled
On the Applicability of ML Fairness Notions.
Karima Makhlouf, Sami Zhioua, Catuscia Palamidessi
2020· preprint· en· arXiv (Cornell University)· Social Sciences
distilled prediction:candidate · noneconsensus · none
9
citations
afffundunlabeled
Unlocking Perceived Algorithmic Autonomy-Support: Scale Development and Validation
Nura Jabagi, Anne‐Marie Croteau, Luc K. Audebrand, Josianne Marsan
2021· article· en· Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences· Social Sciences
distilled prediction:candidate · metaepi_narrow+sts+scholarly_communication+open_scienceconsensus · sts
9
citations
affunlabeled
Desirable Inefficiency
2019· article· en· Florida law review· Social Sciences
distilled prediction:candidate · insufficient_payloadconsensus · insufficient_payload
9
citations
venueno affunlabeled
AI Opaqueness: What Makes AI Systems More Transparent?
Victoria L. Rubin
2020· article· en· Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI· Social Sciences
distilled prediction:candidate · metaresearch+scholarly_communicationconsensus · scholarly_communication
8
citations
affunlabeled
Are Sentient AIs Persons?
Mark Kingwell
2020· reference-entry· en· Oxford University Press eBooks· Social Sciences
distilled prediction:candidate · metaepi_narrow+stsconsensus · none
8
citations
affunlabeled
THE ETHICS OF EMOTION IN AI SYSTEMS
Luke Stark, Jesse Hoey
2019· article· en· AoIR Selected Papers of Internet Research· Social Sciences
distilled prediction:candidate · noneconsensus · none
8
citations

How this was built: Screen · Findings · About