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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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Crime, Illicit Activities, and Governance
Retraction
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Label agreement
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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
fundfunder
venuejournal
aboutaboutness

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

940 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
940 works in the cohort · of 4,299,418page 6 of 19

Labels cover 1 of 940 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 940 of 940 works in this cohort. Predictions are machine_predicted_unvalidated. The Gemma side is a direct model label for every work (title-only); the Codex side is a distilled, calibrated classifier. Candidate is the union; consensus is the intersection.

affaboutunlabeled
Organized crime in business
John Sliter
2006· article· en· Journal of Financial Crime· Social Sciences
machine prediction:candidate · noneconsensus · none
6
citations
aboutno affunlabeled
Chapitre 1. Définir, classifier et mesurer
Jean‐Pierre Guay, Chantal Fredette, Sébastien Dubois
2014· book-chapter· fr· Presses de l’Université de Montréal eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
6
citations
venueno affunlabeled
The Current State of Transnational Organized Crime
Vladimir Golubovskii, Mikhail Fedorovich Kostyuk, Elena Kunts
2020· article· en· International Journal of Criminology and Sociology· Social Sciences
machine prediction:candidate · noneconsensus · none
5
citations
aboutno affunlabeled
Identifying money laundering
Stephen Sterling
2015· article· en· Journal of Money Laundering Control· Social Sciences
machine prediction:candidate · noneconsensus · none
5
citations
affunlabeled
What Gangs Aren’t
Martin Bouchard, Karine Descormiers, Alysha Girn
2024· book-chapter· en· Oxford University Press eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
4
citations
affno abstractunlabeled
Interrogation Methods and Terror Networks
Mariagiovanna Baccara, Heski Bar‐Isaac
2008· article· en· SSRN Electronic Journal· Social Sciences
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Le monde à l'envers ?
Rémi Boivin
2010· article· fr· Déviance et Société· Social Sciences
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Gangs and Crime Deterrence
Abdalla Mansour, Nicolas Marceau, Steeve Mongrain
2001· preprint· en· RePEc: Research Papers in Economics· Social Sciences
machine prediction:candidate · noneconsensus · none
4
citations

How this was built: Screen · Findings · About