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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.

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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.

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 5 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.

affno abstractunlabeled
Negotiating privacy preferences in video surveillance systems
Mukhtaj S. Barhm, Nidal Qwasmi, Faisal Z. Qureshi, Khalil El‐Khatib
2011· article· en· International Conference Industrial, Engineering & Other Applications Applied Intelligent Systems· Social Sciences
machine prediction:candidate · noneconsensus · none
17
citations
affunlabeled
Pseudonym Technology for E-Services
Ronggong Song, Larry Korba, George Yee
2011· book-chapter· en· IGI Global eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
16
citations
aboutno affunlabeled
Policing and Social Media
Andrew Goldsmith, Katina Michael, Stuart D. Flynn
2016· book· en· Lexington Books· Social Sciences
machine prediction:candidate · noneconsensus · none
16
citations
aboutno affunlabeled
Guarding Privacy on the Internet
Madan Lal Bhasin
2006· article· en· Global Business Review· Social Sciences
machine prediction:candidate · noneconsensus · none
16
citations
aboutno affunlabeled
Policing and Social Media
Christopher J. Schneider
2016· book· en· Lexington Books· Social Sciences
machine prediction:candidate · noneconsensus · none
15
citations
affunlabeled
Why Where You Are Matters
David Lyon
2011· book-chapter· en· IGI Global eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
15
citations
affunlabeled
Owner-controlled information
Carrie Gates, Jacob Slonim
2003· article· en· Social Sciences
machine prediction:candidate · noneconsensus · none
15
citations
affno abstractunlabeled
Data Ownership
Teresa Scassa
2018· article· en· SSRN Electronic Journal· Social Sciences
machine prediction:candidate · noneconsensus · none
14
citations
affno abstractunlabeled
Privacy in Online Social Networks
Elie Raad, Richard Chbeir
2013· book-chapter· en· Lecture notes in social networks· Social Sciences
machine prediction:candidate · noneconsensus · none
14
citations
affunlabeled
Are Online Privacy Policies Readable?
M. Sumeeth, Ranjit Singh, James Miller
2010· article· en· International Journal of Information Security and Privacy· Social Sciences
machine prediction:candidate · noneconsensus · none
14
citations

How this was built: Screen · Findings · About