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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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Auditing, Earnings Management, Governance
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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
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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.

3,740 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.
3,740 works in the cohort · of 4,299,418page 19 of 75

Labels cover 11 of 3,740 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 3,740 of 3,740 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
On the relevance and comparability of segment data
Neil Garrod, C. R. Emmanuel
2002· article· en· ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam)· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
33
citations
affno abstractunlabeled
Measuring Corporate Culture Using Machine Learning
Kai Li, Feng Mai, Rui Shen, Xinyan Yan
2018· article· en· SSRN Electronic Journal· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
33
citations
venueno affunlabeled
Does Audit Quality Matters in Malaysian Public Sector Auditing?
Aida Hazlin Ismail, Natasha Binti Muhammad Merejok, Muhamad Ridhuan Mat Dangi, Shukriah Saad
2019· article· en· International Journal of Financial Research· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
33
citations
affno abstractunlabeled
Auditor Choice in Politically Connected Firms
Omrane Guedhami, Jeffrey Pittman, Walid Saffar
2012· article· en· SSRN Electronic Journal· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
32
citations
affunlabeled
Culture and corporate voluntary reporting
Monir Mir, Bikram Chatterjee, Abu Shiraz Rahaman
2009· article· en· Managerial Auditing Journal· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
32
citations
affunlabeled
Do Analysts’ Notes Provide New Information?
Gus De Franco, Ole‐Kristian Hope
2011· article· en· Journal of Accounting Auditing & Finance· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
31
citations
affunlabeled
Determinants of the Readability of SOX 404 Reports
J. Efrim Boritz, Louise Hayes, Lev M. Timoshenko
2016· article· en· Journal of Emerging Technologies in Accounting· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
31
citations
venueno affunlabeled
Hedge Fund Intervention and Accounting Conservatism
Agnes Cheng, Henry He Huang, Yinghua Li
2014· article· en· Contemporary Accounting Research· Business, Management and Accounting
machine prediction:candidate · noneconsensus · none
31
citations

How this was built: Screen · Findings · About