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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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Computational and Text Analysis Methods
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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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venuejournal
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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.

514 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.
514 works in the cohort · of 4,299,418page 1 of 11

Labels cover 5 of 514 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 514 of 514 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
Language and Ideology in Congress
Daniel Diermeier, Jean-François Godbout, Bei Yu, Stefan Kaufmann
2011· article· en· British Journal of Political Science· Social Sciences
machine prediction:candidate · noneconsensus · none
168
citations
affno abstractunlabeled
Exploring Big Historical Data
Shawn Graham, Ian Milligan, Scott Weingart
2014· book· en· IMPERIAL COLLEGE PRESS eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
66
citations
afffundaboutunlabeled
Frontiers in data analytics for adaptation research: Topic modeling
Alexandra Lesnikowski, Ella Belfer, Emma Rodman, Julie Smith, Robbert Biesbroek, John Wilkerson +2 more
2019· article· en· Wiley Interdisciplinary Reviews Climate Change· Social Sciences
machine prediction:candidate · noneconsensus · none
64
citations
affaboutunlabeled
Digitization of the Canadian Parliamentary Debates
Kaspar Beelen, Timothy Alberdingk Thijm, Christopher Cochrane, Kees Halvemaan, Graeme Hirst, Michael Kimmins +6 more
2017· article· en· Canadian Journal of Political Science· Social Sciences
machine prediction:candidate · noneconsensus · none
56
citations
fundno affunlabeled
Measuring discursive influence across scholarship
Aaron Gerow, Yuening Hu, Jordan Boyd‐Graber, David M. Blei, James A. Evans
2018· article· en· Proceedings of the National Academy of Sciences· Social Sciences
machine prediction:candidate · bibliometricsconsensus · none
54
citations
affno abstractunlabeled
What are narratives good for?
John Beatty
2016· article· en· Studies in History and Philosophy of Science Part C Studies in History and Philosophy of Biological and Biomedical Sciences· Social Sciences
machine prediction:candidate · noneconsensus · none
52
citations
affaboutunlabeled
2019 Canadian Election Study (CES) - Online Survey
Laura B. Stephenson, Allison Harell, Daniel Rubenson, Peter John Loewen
2020· dataset· en· Harvard Dataverse· Social Sciences
machine prediction:candidate · noneconsensus · none
40
citations
affvenueunlabeled
Beyond Frequency: Perceived Realism and the <i>CSI</i> Effect
Evelyn M. Maeder, Richard Corbett
2014· article· en· Canadian Journal of Criminology and Criminal Justice/La Revue canadienne de criminologie et de justice pénale· Social Sciences
machine prediction:candidate · noneconsensus · none
29
citations
afffundunlabeled
The Computational Thematic Analysis Toolkit
Robert P. Gauthier, James R. Wallace
2022· article· en· Proceedings of the ACM on Human-Computer Interaction· Social Sciences
machine prediction:candidate · noneconsensus · none
23
citations
affunlabeled
AI-Generated Popular Culture
Marcel Danesi
2024· book· en· Social Sciences
machine prediction:candidate · noneconsensus · none
22
citations
aboutno affunlabeled
Keeping in Touch
2019· book· en· Advances in historical sociolinguistics· Social Sciences
machine prediction:candidate · noneconsensus · none
20
citations

How this was built: Screen · Findings · About