MétaCan
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.

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
Reading and Literacy Development
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.

2,605 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.
2,605 works in the cohort · of 4,299,418page 48 of 53

Labels cover 2 of 2,605 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 2,605 of 2,605 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
Word Superiority Effect Overcomes Crowding
Josée Rivest, June Cutler, Alexandre Bodet, Patrick Cavanagh
2024· preprint· en· SSRN Electronic Journal· Psychology
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
From the Editor
Nickola Wolf Nelson, Katharine G. Butler
2006· article· en· Topics in Language Disorders· Psychology
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Introduction
Ute Ward, Bob Perry
2020· book-chapter· en· Psychology
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
Willed Learning
Carlo Ricci, Brooke Growden, Debbie Michaud
2020· book-chapter· en· Advances in early childhood and K-12 education· Psychology
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Units of word recognition
Xavier Morin Duchesne, Daniel Fiset, Martin Arguin, Frédéric Gosselin
2013· article· en· Journal of Vision· Psychology
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Lexicality as a Determinant of the Category-Order Effect
Michael Henighan, Robert Thomson, Jordan Richard Schoenherr, Sylvain Pronovost
2006· article· en· eScholarship (California Digital Library)· Psychology
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Early Childhood Language and Literacy
Anne Shaughnessy, Dixie Sanger, Carrie Matteucci, Mitzi Ritzman
2004· article· en· ASHA Leader· Psychology
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Reading-spelling acquisition in French
Liliane Sprenger-Charolles, Alain Desrochers, Edouard Gentaz
2018· article· en· HAL (Le Centre pour la Communication Scientifique Directe)· Psychology
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Honoring All Learners
Jan Lacina, Robin Griffith
2016· article· en· The Reading Teacher· Psychology
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About