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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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Education and Critical Thinking Development
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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
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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.

2,368 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.
2,368 works in the cohort · of 4,299,418page 32 of 48

Labels cover 9 of 2,368 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 2,368 of 2,368 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.

affno abstractunlabeled
Truth, Value and the Aim of Inquiry
Matthew S. Bedke
2024· article· en· Analysis· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Finding Support for Writing the Thesis
Lorrie Blair
2016· book-chapter· en· SensePublishers eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
Methodological Meeting of the Minds (M3): A Teaching & Learning Series
Victoria Burns, Deinera Exner‐Cortens, C. E. Walsh, Dorothy Badry, Angélique Jenney, Regine King +2 more
2019· article· en· Libraries and Cultural Resources (University of Calgary)· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Shaking up story time
Bartlomiej A. Lenart, Carla J. Lewis
2019· article· en· Journal of Information Literacy· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affvenueunlabeled
Trust in Education: Truths and Values
Marc Imbeault
2013· article· en· Canadian Journal of University Continuing Education· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
PROFESSIONAL READING
Sarah Lindstrom Johnson, Beatriz Fernández, Anne‐Marie Deitering, Samantha Hines, J. D. Watson, Melissa Aho +1 more
2008· article· en· Public & Access Services Quarterly· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
Transformative Literacy Proficiency
Maimbolwa Muliwana
2024· article· en· Childhood Education· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Exploring summary writing by introspection
Luxin Yang
2009· article· en· cIRcle (University of British Columbia)· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Issue Information
2024· paratext· en· The Curriculum Journal· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
Conversation & Critical Thinking
Colleen Kerr
2012· article· en· Divergent/Convergent· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Integrity in Public Education
Laurence Stott
2018· article· en· Journal of educational thought.· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About