MétaCan
ENFR
Menu
Cohort builder

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.

Export CSVExport JSONAPI query

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.

Search term
Author
Year range
→
Sort
Language
Type
Field
Venue
Topic
Innovative Education and Learning Practices
Retraction
Abstract
Evidence source
Study design
Label agreement
Label status

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
aboutaboutness

The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

550 results · 1 filter active ·
Results by year
20002025
Publication date
Categories
Machine labels · sparse coverage
Evidence
Language
Type
Citations
An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
550 works in the cohort · of 4,299,418page 1 of 11

Labels cover 1 of 550 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 550 of 550 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.

affunlabeled
Collaborative design as a form of professional development
Joke Voogt, Thérèse Laferrière, Alain Breuleux, Rebecca C. Itow, Daniel T. Hickey, Susan McKenney
2015· article· en· Instructional Science· Social Sciences
machine prediction:candidate · noneconsensus · none
312
citations
affunlabeled
Learning about networked learning communities
Steven T. Katz, Lorna Earl
2010· article· en· School Effectiveness and School Improvement· Social Sciences
machine prediction:candidate · noneconsensus · none
245
citations
affunlabeled
Re‐thinking the “thing”
Tara Fenwick
2010· article· en· Journal of Workplace Learning· Social Sciences
machine prediction:candidate · noneconsensus · none
224
citations
affunlabeled
Reflections on activity theory
David Bakhurst
2009· article· en· Educational Review· Social Sciences
machine prediction:candidate · noneconsensus · none
184
citations
venueno affunlabeled
Theory Research and Practice
Dianne Oberg
2007· article· en· School Libraries Worldwide· Social Sciences
machine prediction:candidate · noneconsensus · none
134
citations
affunlabeled
Toward a Theory of <i>Experience</i>
Wolff‐Michael Roth, Alfredo Jornet
2013· article· en· Science Education· Social Sciences
machine prediction:candidate · noneconsensus · none
131
citations
affunlabeled
When I say … community of practice
Heather Buckley, Yvonne Steinert, Glenn Regehr, Laura Nimmon
2019· article· en· Medical Education· Social Sciences
machine prediction:candidate · noneconsensus · none
75
citations
affno abstractunlabeled
Learning Communities In Practice
Clive Beck, Anne Reilley Freese, Clare Kosnik, Anastasia P. Samaras
2008· book· en· Social Sciences
machine prediction:candidate · noneconsensus · none
54
citations
affunlabeled
Vygotsky and Culture
Michael Cole, Natalia Gajdamaschko
2007· book-chapter· cs· Cambridge University Press eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
48
citations
next →

How this was built: Screen · Findings · About