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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.

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

1,631 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
1,631 works in the cohort · of 4,299,418page 22 of 33

Labels cover 1 of 1,631 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 1,631 of 1,631 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.

afffundunlabeled
A model of risk sharing in a dual labor market
Jonathan Créchet
2024· article· en· Journal of Monetary Economics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Behind the North-South divide: A decomposition analysis
David Vizer
2011· article· en· Munich Personal RePEc Archive (Ludwig Maximilian University of Munich)· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Minimum Wage Increases and Vacancies
Marianna Kudlyak, Murat Tasci, Didem Tüzemen
2022· article· en· Federal Reserve Bank of San Francisco, Working Paper Series· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
1
citations
fundno affunlabeled
Employer Transit Subsidy Study: Main Report
Peter Hall, Anthony Perl, Karen Sawatzky
2020· article· en· Summit (Simon Fraser University)· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Search, technology choice, and unemployment
Constantine Angyridis, Haiwen Zhou
2022· article· en· International Studies of Economics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
1
citations
venueno affunlabeled
Reform and Challenges in China’s Labor Market
Lin Yuan, Shaobo Wang
2014· article· en· Studies in sociology of science· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Skill Heterogeneity and Equilibrium Unemployment
Rebecca Riley, Garry Young
2003· preprint· en· RePEc: Research Papers in Economics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Employer Learning and the 'Importance' of Skills
Audrey Light, Andrew McGee
2012· article· en· SSRN Electronic Journal· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
fundno affunlabeled
Gender, careers and peers' gender mix
2024· other· en· London School of Economics and Political Science Research Online (London School of Economics and Political Science)· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
How Sticky Wages in Existing Jobs Can Affect Hiring
Mark Bils, Yongsung Chang, Sun-Bin Kim
2014· article· en· American Economic Journal Macroeconomics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
PROSPERED Dataset: Unemployment Benefits
Arijit Nandi, Ilona Vincent, Efe Atabay
2023· dataset· en· Harvard Dataverse· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About