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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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Social Media and Politics
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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.

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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.

2,257 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.
2,257 works in the cohort · of 4,299,418page 36 of 46

Labels cover 12 of 2,257 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 2,257 of 2,257 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.

aboutno affunlabeled
How Topics Affect Twitter Attention
Michal Fishkin, Jennifer Ou, Andrew Zhu
2017· dataset· en· Figshare· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
How Topics Affect Twitter Attention
Fishkin Michal, Ou Jennifer
2017· article· en· Figshare· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Instagram in Four Countries
Shelley Boulianne
2021· dataset· en· Figshare· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Equity, Diversity and Inclusion Online
Robyn Ruttenberg-Rozen, Allyson Eamer
2022· book-chapter· en· University of Ontario Insitute of Technology eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
The use of Twitter in the Danish EP elections 2014
Jakob Linaa Jensen, Jacob Ørmen, Stine Lomborg
2016· article· en· Research at the University of Copenhagen (University of Copenhagen)· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
The Downfall of Digital Democracy?
Andreea Musulan
2024· dissertation· TSpace· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
МУЛЬТИКУЛЬТУРАЛІЗМ ЯК ЧИННИК ДЕМОКРАТИЧНОГО РОЗВИТКУ СУСПІЛЬСТВА ТА РОЗБУДОВИ КІБЕРПРОСТОРУ У КОНТЕКСТІ СУЧАСНОЇ ЕТНОПОЛІТИКИ
Ірина КРИНИЧНА
2025· article· Наукові праці Міжрегіональної Академії управління персоналом Політичні науки та публічне управління· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Forandrer Facebook partiernes forhold til vælgerne?
Karina Kosiara-Pedersen, Lars Duvander Højholt
2011· article· da· Research at the University of Copenhagen (University of Copenhagen)· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
9781040305140.pdf
2024· other· en· OAPEN (The OAPEN Foundation)· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Existing Analytical Frameworks for Information Behaviour Don’t Fully Explain HIV/AIDS Information Exchange in Rural Communities in Ontario, Canada. A Review of: Veinot, T., Harris, R., Bella, L., Rootman, I., & Krajnak, J. (2006). HIV/AIDS Information exchange in rural communities: Preliminary findings from a three‐province study. Canadian Journal of Information and Library Science, 30(3/4), 271‐290.
Kate Kelly
2010· review· en· DOAJ (DOAJ: Directory of Open Access Journals)· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Votefoot survey data for POP.tab
Christopher J. Anderson, Luc Arrondel, André Blais, Jean‐François Daoust, Jean‐François Laslier, Karine Van der Straeten
2019· dataset· en· Harvard Dataverse· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
Parliamentary Discourse Quality Index
Christopher Greenaway
2025· dissertation· TSpace (University of Toronto)· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
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How this was built: Screen · Findings · About