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
Corruption and Economic 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.

730 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.
730 works in the cohort · of 4,299,418page 1 of 15

Labels cover 4 of 730 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 730 of 730 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
Corruption: A Review
Arvind K. Jain
2001· review· en· Journal of Economic Surveys· Social Sciences
machine prediction:candidate · noneconsensus · none
1,393
citations
afffundunlabeled
Monitoring Corruptible Politicians
Gustavo J. Bobonis, Luis R. Cámara Fuertes, Rainer Schwabe
2016· article· en· American Economic Review· Social Sciences
machine prediction:candidate · noneconsensus · none
217
citations
affunlabeled
Measuring Transparency
James R. Hollyer, B. Peter Rosendorff, James Raymond Vreeland
2014· article· en· Political Analysis· Social Sciences
machine prediction:candidate · noneconsensus · none
211
citations
affunlabeled
LETTER GRADING GOVERNMENT EFFICIENCY
Alberto Chong, Rafael La Porta, Florencio López‐de‐Silanes, Andrei Shleifer
2014· article· en· Journal of the European Economic Association· Social Sciences
machine prediction:candidate · noneconsensus · none
161
citations
afffundunlabeled
Greasing the Palm
Nina Mažar, Pankaj Aggarwal
2011· article· en· Psychological Science· Social Sciences
machine prediction:candidate · noneconsensus · none
144
citations
affunlabeled
The Emergence of Political Accountability*
Chris Bidner, Patrick François
2013· article· en· The Quarterly Journal of Economics· Social Sciences
machine prediction:candidate · noneconsensus · none
87
citations
affno abstractunlabeled
Illicit money flows as motives for FDI
M. Fabricio Perez, Josef C. Brada, Zdeněk Drábek
2011· article· en· Journal of Comparative Economics· Social Sciences
machine prediction:candidate · noneconsensus · none
82
citations
fundno affno abstractunlabeled
Mining and corruption
Andrea Petermann, Juan Ignacio Guzmán, John E. Tilton
2007· article· en· Resources Policy· Social Sciences
machine prediction:candidate · noneconsensus · none
75
citations
next →

How this was built: Screen · Findings · About