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Record W7115173464 · doi:10.51644/9781771126564

Canada and the Blackface Atlantic

2025· book· W7115173464 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typebook
Language
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsBlackfaceDanceEntertainmentFolk songSingingMasking (illustration)

Abstract

fetched live from OpenAlex

Canada and the Blackface Atlantic traces the origins of theatre, dance, and concert singing in Canada and their connection to British and American song and dance traditions. When theatrical acts first appeared in the late eighteenth century, chattel slavery had transformed into mass entertainment on minstrel stages across the Atlantic world. As railroads and theatres were built, local blackface troupes emerged alongside touring British and American acts. By the 1850s, blackface theatre could be found in remote Western outposts to stages in Central and Maritime Canada. This is one of the first books to connect the rise of Canadian blackface minstrelsy with the emergence of Black singers, and choral groups. It describes how Black performers who assumed minstrelsy’s mask remapped plantation slavery on Canadian stages. It begins with the conflicts that shaped North America – the American Revolutionary War, and the War of 1812. Next, it connects these origins with eighteenth-century British immigration, which brought folk dances and masking traditions to North America. From there, it unmasks when and how “Jim Crow” became an Atlantic world sensation, which set the stage for blackface to expand. Finally, it considers how Black acts reimagined the parameters of their own freedom.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.068
Threshold uncertainty score0.493

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0170.010
Scholarly communication0.0070.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0190.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.180
Teacher spread0.176 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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