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Record W4205958138 · doi:10.5206/mf.v7i1.14365

Sarah Bernhardt’s presence in Montréal Québec

2022· article· en· W4205958138 on OpenAlexaffvenueabout
Amanda Lee, Geneviève De Viveiros

Bibliographic record

VenueMouvances Francophones · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicFrench Literature and Poetry
Canadian institutionsWestern University
Fundersnot available
KeywordsJudaismYiddishContext (archaeology)ImmigrationReputationHistoryArtArt historyLiteratureLawPolitical scienceArchaeology

Abstract

fetched live from OpenAlex

During the summer 2021 and under the direction of Geneviève De Viveiros, Amanda Lee produced a large portion of this study based on Sarah Bernhardt’s performances in Canada as they occurred between 1800 and 1918 and were studied by John Hare and Ramon Hathron, who included in their records her repertoire and the dates of her performances as well as critical opinions from various print sources. When Montréal constructed its francophone theater and its artistic infrastructure it quickly caught up with anglophone venues. Catholic institutions became increasingly adverse to Bernhardt deemed unworthy to represent the desired link to the French Catholic cultural bridge with the former motherland, in a context that revealed itself anti-women as well as anti-Semitic for this respected actress of Jewish ancestry, yet so famous for her French elocution. Bernhardt’s sulphureous reputation festered when she was reported as accusing people from Québec to be Iroquois or under religious guidance, setting her friend Louis Fréchette apart from the benighted crowd. Conversely, contrary to the increasingly negative reception of Bernhardt’s performances in the early 1900s, and the association of Jewish immigrants with Anglophone communities, Yiddish theatre saw a massive and fragmented growth between 1905-1910. By 1913, there were a total of three permanent professional Yiddish theatre troupes in the city.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.426
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0150.000

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 head0.009
GPT teacher head0.179
Teacher spread0.171 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations0
Published2022
Admission routes3
Has abstractyes

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