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
Gender, Labor, and Family Dynamics
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.

1,528 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.
1,528 works in the cohort · of 4,299,418page 19 of 31

Labels cover 1 of 1,528 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 1,528 of 1,528 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.

aboutno affno abstractunlabeled
How Much Does Work Pay at Older Ages?
Damir Cosic
2019· book-chapter· en· Social Sciences
machine prediction:candidate · noneconsensus · none
1
citations
venueaboutno affunlabeled
Can We Afford to Pay for Social Programs?
John Smithin
2004· article· en· Studies in Political Economy· Social Sciences
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Female Executives and the Motherhood Penalty
Seth Murray, Danielle H. Sandler, Matthew Staiger
2023· article· en· The Journal of Human Resources· Social Sciences
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
THREE ESSAYS ON INCOME AND WEALTH
Chunling Fu
2008· dissertation· en· Summit (Simon Fraser University)· Social Sciences
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Promoting Equity in Economic Rights
Elisa Scalise, Renée Giovarelli
2012· book-chapter· en· Cambridge University Press eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
The United States
Joshua T. McCabe
2018· book· en· Oxford University Press eBooks· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
1
citations
affvenueaboutunlabeled
Determinants of Weekly Work Hours in Canada
Keith Newton, Norm Leckie
2005· article· en· Relations industrielles· Social Sciences
machine prediction:candidate · noneconsensus · none
1
citations
affvenueno abstractunlabeled
Food taxes: Too easy a solution
Daniel‐Mercier Gouin, C. Gervais
2011· article· en· Canadian Journal of Diabetes· Social Sciences
machine prediction:candidate · noneconsensus · none
1
citations

How this was built: Screen · Findings · About