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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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Language, Discourse, Communication Strategies
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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
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.

990 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.
990 works in the cohort · of 4,299,418page 4 of 20

Labels cover 0 of 990 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 990 of 990 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
Ethics in Linguistics
Alexandra D’Arcy, Emily M. Bender
2022· article· en· Annual Review of Linguistics· Arts and Humanities
machine prediction:candidate · research_integrityconsensus · none
26
citations
affvenueaboutunlabeled
Emotive Language in Argumentation
Michael A. Gilbert
2014· article· en· Informal Logic· Arts and Humanities
machine prediction:candidate · noneconsensus · none
25
citations
affunlabeled
The Extremes of Insubordination
Laurel J. Brinton
2014· article· en· Journal of English Linguistics· Arts and Humanities
machine prediction:candidate · noneconsensus · none
24
citations
affunlabeled
The emergence of implicit meaning
Pierre Larrivée, Patrick Duffley
2014· article· en· International Journal of Corpus Linguistics· Arts and Humanities
machine prediction:candidate · noneconsensus · none
24
citations
aboutno affunlabeled
Transitions with “Okay”
Tetyana Reichert, Grit Liebscher
2018· book-chapter· en· Pragmatics & beyond. New series· Arts and Humanities
machine prediction:candidate · noneconsensus · none
23
citations
affunlabeled
Epistemics
Jack Sidnell
2015· other· en· The International Encyclopedia of Language and Social Interaction· Arts and Humanities
machine prediction:candidate · noneconsensus · none
23
citations
affunlabeled
What counts as (contact-induced) change
Shana Poplack, Lauren Zentz, Nathalie Dion
2011· article· en· Bilingualism Language and Cognition· Arts and Humanities
machine prediction:candidate · noneconsensus · none
22
citations
afffundunlabeled
BEYOND LINGUISTIC FEATURES
Charlie Nagle, Pavel Trofimovich, Mary Grantham O’Brien, Sara Kennedy
2021· article· en· Studies in Second Language Acquisition· Arts and Humanities
machine prediction:candidate · noneconsensus · none
20
citations
affunlabeled
Measuring the Capacity to Love: Development of the CTL-Inventory
Nestor D. Kapusta, Konrad S. Jankowski, Viktoria Wolf, Magalie Chéron-Le Guludec, Madlen Lopatka, Christopher Hammerer +4 more
2018· article· en· Frontiers in Psychology· Arts and Humanities
machine prediction:candidate · noneconsensus · none
20
citations
affunlabeled
Conversation Analysis
Jack Sidnell
2016· reference-entry· en· Oxford Research Encyclopedia of Linguistics· Arts and Humanities
machine prediction:candidate · noneconsensus · none
20
citations
aboutno affunlabeled
It’s not all about you
2019· book· en· Topics in address research· Arts and Humanities
machine prediction:candidate · noneconsensus · none
20
citations

How this was built: Screen · Findings · About