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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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Employment and Welfare Studies
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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.

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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.

3,193 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.
3,193 works in the cohort · of 4,299,418page 41 of 64

Labels cover 13 of 3,193 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 3,193 of 3,193 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.

aboutno affunlabeled
Women's Hidden Work Linda Delp
Linda Delp
2011· article· en· NEW SOLUTIONS A Journal of Environmental and Occupational Health Policy· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
venueno affno abstractunlabeled
Commentaire sur le texte de Zygmunt Bauman
Michael Herzfeld
2003· article· fr· Anthropologie et Sociétés· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Health and Brexit
John Wildman, Rachel Baker, Cam Donaldson
2017· editorial· en· Health Economics· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
venueno affunlabeled
Labour market conditions and adult health in Mexico
Pınar Mine Güneş, Magda Tsaneva
2022· article· en· Canadian Journal of Economics/Revue canadienne d économique· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Unemployment Insurance and Macro-Financial (In)Stability
Gazi Kabaş, Yavuz Arslan, Ahmet Değerli, Burhanettin Kuruşçu, Bülent Güler
2024· article· en· SSRN Electronic Journal· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
venueno affunlabeled
Chômage et usages de substances psychoactives
Virginie Althaus, Sébastien Ladreyt, Yannick Le Hénaff, Joëlle Mezza, Dominique Lhuilier
2020· article· fr· Perspectives interdisciplinaires sur le travail et la santé· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affno abstractunlabeled
Halifax: Scaling Inequality
Jill L. Grant, Howard Ramos
2020· book-chapter· en· University of British Columbia Press eBooks· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Prospects for the UK Economy
Simon Kirby, Rachel Whitworth
2011· article· en· National Institute Economic Review· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
The Healthcare Sector
Giliberto Capano, Anthony R. Zito, Federico Toth, Jeremy Rayner
2022· book-chapter· en· International series on public policy· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
affaboutunlabeled
Migrant Friendly Maternity Care in a Western Urban Centre
Alain Gagnon, Sandra Peláez, Lisa Merry, Arman Amiri, Kristin Hendricks
2015· article· en· European Journal of Public Health· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations

How this was built: Screen · Findings · About