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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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Education Systems and Policy
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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.

2,366 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.
2,366 works in the cohort · of 4,299,418page 20 of 48

Labels cover 4 of 2,366 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 2,366 of 2,366 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.

venueno affunlabeled
Shelftalkers: Empowering Student Voice
Susan La Marca, Tye Cattanach
2021· article· en· IASL Annual Conference Proceedings· Social Sciences
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Succeeding against SATs
Jon Berry
2019· article· en· FORUM· Social Sciences
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Leveraging remittances for STEM education
Sharma Bk, Bhanu Bhakta Acharya
2025· article· en· American Journal of STEM Education· Social Sciences
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Race for Education
Mark Hunter
2019· book· en· Social Sciences
machine prediction:candidate · noneconsensus · none
1
citations
venueno affno abstractunlabeled
Educational Reforms for the 21st Century
C. A. Bowers
2011· article· en· The Trumpeter· Social Sciences
machine prediction:candidate · noneconsensus · none
1
citations
affvenueaboutunlabeled
Reading for the Technical Workplace
Nathan J. Devos
2023· article· en· TESL Canada Journal· Social Sciences
machine prediction:candidate · noneconsensus · none
1
citations
venueno affunlabeled
Building High Performing Schools: A Case Study
André de Waal, Marco Schreurs, Paul Goossens, Marianne Dirkx
2025· article· en· International Education Studies· Social Sciences
machine prediction:candidate · noneconsensus · none
1
citations
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How this was built: Screen · Findings · About