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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.

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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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Gender Politics and Representation
Retraction
Abstract
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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.

1,356 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
1,356 works in the cohort · of 4,299,418page 25 of 28

Labels cover 0 of 1,356 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 1,356 of 1,356 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
Constructing Plural Solidarities
Semanur Karaman
2016· article· en· SSRN Electronic Journal· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
Canadian Women and the "Charter of Rights"
Doris Anderson
2006· article· fr· Revue nationale de droit constitutionnel· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Gender Communications: He Said...She Said
Jerri McKinney, Gary McCarney
2006· article· en· Women in Engineering ProActive Network· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Mand, Muslim og Minoritet
Fatima Al-Shamasnah, Jinan Hammoude
2023· article· da· Scandinavian Journal of Islamic Studies· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
Public Discourse, Populism and Ontario's Un-Dead Sex Ed
Jessica Wright, Taylor Berzins, Lauren Bialystok, Caileigh Guy
2018· article· en· 2019 Conference of the Canadian Society for the Study of Education· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
Challenges for women in politics
Myrna Driedger
2013· article· en· Canadian parliamentary review· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
A worldwide value divide
Alain Noël, Jean‐Philippe Thérien
2008· book-chapter· en· Cambridge University Press eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Construction of a bibliometric dataset on gender studies
Natsumi S. Shokida, Diego Kozlowski, Vincent Larivière
2024· article· en· SCT Proceedings in Interdisciplinary Insights and Innovations.· Social Sciences
machine prediction:candidate · bibliometricsconsensus · none
0
citations
affunlabeled
validation_tp.tab
Eve Kraicer, Andrew Piper
2019· dataset· en· Harvard Dataverse· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
venueno affno abstractunlabeled
How to Prove You’re a Woman
Shannon Flaherty
2016· article· en· Island writer· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
EES_gender_knowledge_ajpsreplication.tab
Ruth Dassonneville, Ian McAllister
2017· dataset· en· Harvard Dataverse· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
CSES_module 2.tab
Ruth Dassonneville, Ian McAllister
2017· dataset· hu· Harvard Dataverse· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
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How this was built: Screen · Findings · About