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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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Tourism, Volunteerism, and Development
Retraction
Abstract
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Label status

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.

709 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
709 works in the cohort · of 4,299,418page 14 of 15

Labels cover 1 of 709 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 709 of 709 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
Conclusion
Robert A. Stebbins
2017· book-chapter· en· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
International Development Education
Jill Zarestky, Maren Elfert, Daniel Schugurensky
2023· book-chapter· en· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Introduction
2019· book-chapter· en· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Language and Tourism
Kellee Caton, Bryan S. R. Grimwood
2023· book-chapter· en· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Impact – Tourism
Geoffrey Wall
2023· book-chapter· en· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Care and Freedom
2000· article· en· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Working Tourists
Donna James
2022· other· en· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
Tourist Volunteering
Robert A. Stebbins
2025· book-chapter· en· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Community-Based Tourism
Heather Mair
2024· book-chapter· en· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
A New Kind of Sharing
Yingmin Zhao, Arthur J. Hanson
2023· book-chapter· en· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Scholarship
Larry Dwyer, Stephen L. Smith, Philip L. Pearce
2024· book-chapter· en· Social Sciences
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
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