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
Electoral Systems and Political Participation
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.

1,890 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.
1,890 works in the cohort · of 4,299,418page 30 of 38

Labels cover 4 of 1,890 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 1,890 of 1,890 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 affunlabeled
Elections
John C. Courtney
2007· book· en· University of British Columbia Press eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
CCES_Sigma_2012_PartyID.R
Gregory Eady, Peter John Loewen
2020· dataset· en· Harvard Dataverse· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
MakeAppendixTableA11.do
Jennifer Gandhi, Elvin Ong
2019· dataset· fr· Harvard Dataverse· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
List of Figures
2018· paratext· en· University of Toronto Press eBooks· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Figures
2021· book-chapter· en· University of Toronto Press eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
Investing for the Short Term
Alan M. Jacobs
2011· book-chapter· en· Cambridge University Press eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Informative Voting in Large Elections
Ettore Damiano, Hao Li, Wing Suen
2025· preprint· en· SSRN Electronic Journal· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
Economic Voting in Canadian Municipal Elections
Éric Bélanger, Ruth Dassonneville
2024· book-chapter· en· McGill-Queen's University Press eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
fundno affunlabeled
Acknowledgments
2011· book-chapter· en· University of British Columbia Press eBooks· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Results of the 2011 Society Section Elections
Lam Kl, Hong Retired, Bradley Fortner, Rudy Niznansky
2011· article· en· SMPTE Motion Imaging Journal· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
tables_fig_ind.R
Gabriel López-Moctezuma, Léonard Wantchekon, Daniel Rubenson, Thomas Fujiwara, Pe Lero Cecilia
2020· dataset· en· Harvard Dataverse· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
Front Matter
Jean Sandver, Roger C. Anderson, Leo Navin, J.R. Jordan, W Gump, Carl Lieberman +20 more
2024· paratext· en· The Journal of Economics and Politics· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
A Short Introduction to Survey Research
Daniel Stockemer, Jean‐Nicolas Bordeleau
2023· book-chapter· en· Springer texts in political science and international relations· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Social Security and the Third Phase
Richard Johnston, Michael G. Hagen, Kathleen Hall Jamieson
2004· book-chapter· en· Cambridge University Press eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
fundno affno abstractunlabeled
Accountability in Markovian elections
John Duggan, Jean Guillaume Forand
2025· article· en· Games and Economic Behavior· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
The Future of the Canadian Election Studies
Antoine Bilodeau, Thomas J. Scotto, Mebs Kanji
2012· book-chapter· en· University of British Columbia Press eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
Reforming Party and Election Finance in Canada
Lisa Young, Harold Jansen
2011· book-chapter· en· University of British Columbia Press eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
fundaboutno affunlabeled
Acknowledgments
2007· book-chapter· en· University of British Columbia Press eBooks· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
What voting rules do citizens prefer?
2021· dissertation· en· Papyrus : Institutional Repository (Université de Montréal)· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About