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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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Online and Blended Learning
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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
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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.

3,545 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.
3,545 works in the cohort · of 4,299,418page 71 of 71

Labels cover 14 of 3,545 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 3,545 of 3,545 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.

affvenueunlabeled
Integrated Collaborative Tools
Lynn Fujino, Neil Martindale, Sharon Mulder, Clare Woodward, Patrick J. Fahy
2002· article· en· The International Review of Research in Open and Distributed Learning· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affvenueunlabeled
View Entire Issue
Robert M. Bernard Editor
2009· article· fr· Canadian Journal of Learning and Technology· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
Teaching in the Age of Technology
Heather Hemming
2004· article· en· Society for Information Technology & Teacher Education International Conference· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affvenueunlabeled
Editorial — Volume 26, Issue 2
Adnan Qayyum
2025· article· en· The International Review of Research in Open and Distributed Learning· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Open Source Survey Software
Josh Baker
2011· book-chapter· en· IGI Global eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Herding Cats
2011· book-chapter· en· IGI Global eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Pedagogical Evaluation of Online Courses
Shelley Cobbett
2010· article· en· EdMedia: World Conference on Educational Media and Technology· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
TALON: hybrid education
Sandra Abegglen, Clément Bret, Fabian Neuhaus, Krisha Shah, Kylie Wilson
2022· article· en· Journal of Learning Development in Higher Education· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Student Perceptions of Online Practicum
Gabrielle Wilcox, Jennifer Lock
2014· article· en· E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Private Interactions in Online Discussions
Lesley Wilton, Rubaina Khan, Clare Brett, Paul C. Alexander
2022· book-chapter· en· IGI Global eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About