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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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Privacy, Security, and Data Protection
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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.

1,237 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.
1,237 works in the cohort · of 4,299,418page 4 of 25

Labels cover 2 of 1,237 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 1,237 of 1,237 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
Cyborglogging with camera phones
Steve Mann, James Fung, Raymond Lo
2006· article· en· Social Sciences
machine prediction:candidate · noneconsensus · none
24
citations
affunlabeled
Opt out of privacy or "go home"
Fiona Westin, Sonia Chiasson
2019· article· en· Social Sciences
machine prediction:candidate · noneconsensus · none
23
citations
afffundunlabeled
What's the deal with privacy apps?
Hala Assal, Stephanie Hurtado, Ahsan Imran, Sonia Chiasson
2015· article· en· Social Sciences
machine prediction:candidate · noneconsensus · none
23
citations
affaboutunlabeled
Two Notions of Privacy Online
Avner Levin, Patricia Sánchez Abril
2023· article· en· Social Sciences
machine prediction:candidate · noneconsensus · none
22
citations
venueno affunlabeled
Privacy and Social Networking Technology
Richard A. Spinello
2011· article· en· The International Review of Information Ethics· Social Sciences
machine prediction:candidate · noneconsensus · none
20
citations
affunlabeled
Personal but Not Private
Stefanie Duguay
2022· book· en· Oxford University Press eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
20
citations
affunlabeled
Privacy gradients
Kirstie Hawkey, Kori Inkpen
2005· article· en· Social Sciences
machine prediction:candidate · noneconsensus · none
19
citations
affunlabeled
Soft Surveillance, Hard Consent
Ian R. Kerr, Jennifer Barrigar, Jacquelyn Burkell, Katie Black
2006· article· en· SSRN Electronic Journal· Social Sciences
machine prediction:candidate · noneconsensus · none
18
citations
affaboutunlabeled
Reconsidering the Right to Privacy in Canada
Leslie Regan Shade
2007· article· en· Bulletin of Science Technology & Society· Social Sciences
machine prediction:candidate · noneconsensus · none
18
citations

How this was built: Screen · Findings · About