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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 6 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.

affno abstractunlabeled
Job Search Behavior over the Business Cycle
Toshihiko Mukoyama, Christina Patterson, Ayşegül Şahin
2014· article· en· SSRN Electronic Journal· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
25
citations
affunlabeled
Measuring Resource Utilization in the Labor Market
Andreas Hornstein, Marianna Kudlyak, Fabian Lange
2014· article· en· Economic quarterly - Federal Reserve Bank of Richmond· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
24
citations
afffundno abstractunlabeled
Career progression and comparative advantage
Shintaro Yamaguchi
2010· article· en· Labour Economics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
23
citations
affno abstractunlabeled
Differences in On-the-Job Learning Across Firms
Jaime Arellano-Bover, Fernando Saltiel
2021· article· en· SSRN Electronic Journal· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
23
citations
aboutno affunlabeled
Top Incomes in France: booming inequalities?
Camille Landais, Gabrielle Fack, Julien Grenet
2008· article· en· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
22
citations
afffundunlabeled
Market Reforms in the Time of Imbalance
Matteo Cacciatore, Romain Duval, Giuseppe Fiori, Fabio Ghironi
2016· preprint· en· National Bureau of Economic Research· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
21
citations
affunlabeled
Heterogeneity and Learning in Labor Markets
Simon D. Woodcock
2010· article· en· The B E Journal of Economic Analysis & Policy· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
21
citations
affunlabeled
Wage Inequality and Firm Growth
Holger M. Mueller, Paige Ouimet, Elena Simintzi
2015· preprint· en· National Bureau of Economic Research· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
20
citations
affno abstractunlabeled
Second-order statistical discrimination
Tilman Klumpp, Xuejuan Su
2012· article· en· Journal of Public Economics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
20
citations

How this was built: Screen · Findings · About