MétaCan
Menu
Cohort builder

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.

Search term
Author
Year range
Sort
Language
Type
Field
Venue
Topic
Language and cultural evolution
Retraction
Abstract
Evidence source
Study design
Label agreement
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.

495 results · 1 filter active ·
Results by year
20002025
Publication date
Categories
Machine labels · sparse coverage
Evidence
Language
Type
Citations
An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
495 works in the cohort · of 4,299,418page 1 of 10

Labels cover 0 of 495 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 495 of 495 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.

afffundunlabeled
Word learning as Bayesian inference.
Fei Xu, Joshua B. Tenenbaum
2007· article· en· Psychological Review· Social Sciences
machine prediction:candidate · noneconsensus · none
1,055
citations
affunlabeled
Towards a unified science of cultural evolution
Alex Mesoudi, Andrew Whiten, Kevin N. Laland
2006· review· en· Behavioral and Brain Sciences· Social Sciences
machine prediction:candidate · noneconsensus · none
879
citations
affunlabeled
Gene-culture coevolution in the age of genomics
Peter J. Richerson, Robert Boyd, Joseph Henrich
2010· article· en· Proceedings of the National Academy of Sciences· Social Sciences
machine prediction:candidate · noneconsensus · none
388
citations
affno abstractunlabeled
Building social cognitive models of language change
Daniel J. Hruschka, Morten H. Christiansen, Richard A. Blythe, William Croft, Paul Heggarty, Salikoko S. Mufwene +2 more
2009· review· en· Trends in Cognitive Sciences· Social Sciences
machine prediction:candidate · noneconsensus · none
235
citations
affaboutunlabeled
The Science of Language
Noam Chomsky, James McGilvray
2012· book· en· Cambridge University Press eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
193
citations
affunlabeled
Sociality influences cultural complexity
Michael Muthukrishna, Ben W. Shulman, Vlad Gabrie Vasilescu, Joseph Henrich
2013· article· en· Proceedings of the Royal Society B Biological Sciences· Social Sciences
machine prediction:candidate · noneconsensus · none
189
citations
fundno affunlabeled
The Pace of Cultural Evolution
Charles Perreault
2012· article· en· PLoS ONE· Social Sciences
machine prediction:candidate · noneconsensus · none
181
citations
fundno affunlabeled
The role of semantic diversity in lexical organization.
Michael N. Jones, Brendan T. Johns, Gabriel Recchia
2012· article· en· Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale· Social Sciences
machine prediction:candidate · noneconsensus · none
156
citations
affunlabeled
The Tanzanian Rift Valley area
Roland Kießling, Maarten Mous, Derek Nurse
2007· book-chapter· en· Cambridge University Press eBooks· Social Sciences
machine prediction:candidate · noneconsensus · none
152
citations
affunlabeled
Algorithms in the historical emergence of word senses
Christian Ramiro, Mahesh Srinivasan, Barbara C. Malt, Yang Xu
2018· article· en· Proceedings of the National Academy of Sciences· Social Sciences
machine prediction:candidate · noneconsensus · none
107
citations
affunlabeled
The uses and abuses of tree thinking in cultural evolution
Cara L. Evans, Simon J. Greenhill, Joseph Watts, Johann‐Mattis List, Carlos A. Botero, Russell D. Gray +1 more
2021· review· en· Philosophical Transactions of the Royal Society B Biological Sciences· Social Sciences
machine prediction:candidate · noneconsensus · none
103
citations
affunlabeled
The structure of cross-cultural musical diversity
Tom Rzeszutek, Patrick E. Savage, Steven Brown
2011· article· en· Proceedings of the Royal Society B Biological Sciences· Social Sciences
machine prediction:candidate · noneconsensus · none
100
citations
affunlabeled
A ‘Galilean’ science of language
Christina Behme
2014· article· en· Journal of Linguistics· Social Sciences
machine prediction:candidate · noneconsensus · none
92
citations
aboutno affunlabeled
Lexical forces shaping the evolution of grammar
Marianne Mithun
2001· book-chapter· en· Amsterdam studies in the theory and history of linguistic science. Series 4, Current issues in linguistic theory· Social Sciences
machine prediction:candidate · noneconsensus · none
78
citations
fundno affunlabeled
Polite Speech Emerges From Competing Social Goals
Erica J. Yoon, Michael Tessler, Noah D. Goodman, Michael C. Frank
2020· article· en· Open Mind· Social Sciences
machine prediction:candidate · noneconsensus · none
66
citations

How this was built: Screen · Findings · About