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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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The United States and Canada
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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.

13 results · 1 filter active ·
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20192019
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Categories
Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
13 works in the cohort · of 4,299,418page 1 of 1

Labels cover 0 of 13 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 13 of 13 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
Political Culture and Values
Russell J. Dalton
2019· book-chapter· en· The United States and Canada· Social Sciences
machine prediction:candidate · noneconsensus · none
3
citations
aboutno affunlabeled
Environmental Policy
Kathryn Harrison
2019· book-chapter· en· The United States and Canada· Environmental Science
machine prediction:candidate · noneconsensus · none
3
citations
aboutno affunlabeled
Managing Diversity
Irene Bloemraad, Doris Marie Provine
2019· book-chapter· en· The United States and Canada· Social Sciences
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Assessing Performance
Keith Banting, Jack H. Nagel, Chelsea Schafer, Daniel Westlake
2019· book-chapter· en· The United States and Canada· Social Sciences
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Bureaucratic Influence and Policymaking
John McAndrews, Bert A. Rockman, Colin Campbell
2019· book-chapter· en· The United States and Canada· Social Sciences
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Introduction
Paul J. Quirk
2019· book-chapter· en· The United States and Canada· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Healthcare
Antonia Maioni, Theodore R. Marmor
2019· book-chapter· en· The United States and Canada· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Electoral and Party Systems
André Blais, Shaun Bowler, Bernard Grofman
2019· book-chapter· en· The United States and Canada· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Federalism
Richard Simeon, Beryl A. Radin
2019· book-chapter· en· The United States and Canada· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Economic Policy
William R. Keech, William Scarth
2019· book-chapter· en· The United States and Canada· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Lessons of Comparison
Paul J. Quirk
2019· book-chapter· en· The United States and Canada· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Morality Issues
Gary Mucciaroni, Francesca Scala
2019· book-chapter· en· The United States and Canada· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About