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Record W2560068481 · doi:10.7202/1037880ar

Le Congrès juif canadien et l’hostilité à l’immigration juive dans l’immédiat après-guerre (1945-1948)1

2016· article· fr· W2560068481 on OpenAlexaffvenueabout
Antoine Burgard

Bibliographic record

VenueGlobe Revue internationale d’études québécoises · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

La politique migratoire canadienne des années 1930 et 1940 est la plus restrictive et sélective de l’histoire du pays, notamment en raison de son hostilité envers les populations migrantes juives. La question de l’antisémitisme au Canada et au Québec ne peut donc se poser sans revenir sur la position d’Ottawa en matière migratoire. Dans cet article, nous souhaitons examiner non pas les manifestations de cette hostilité, mais la manière dont celle-ci fut perçue et combattue par le Congrès juif canadien (CJC), alors principale organisation de la communauté, entre 1945 et 1948. En effet, quelle image le CJC a-t-il vraiment de l’hostilité de l’opinion publique et des mécanismes discriminatoires de la politique migratoire canadienne ? Et comment cette perception façonne-t-elle durablement sa stratégie de lutte contre l’antisémitisme et l’hostilité à l’immigration juive ainsi que ses rapports avec le gouvernement King ? L’analyse fine du travail des principaux cadres du CJC sur cette question permet de jeter un éclairage nouveau sur la place de l’organisation au sein du judaïsme canadien, de mieux cerner ses relations avec la presse et, surtout, ses rapports avec un gouvernement et une administration pour le moins hostiles à l’entrée de migrants juifs au Canada.

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)0.002
metaresearch head score (Gemma)0.003
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.355
Threshold uncertainty score0.715

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0110.007
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0100.000

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 head0.026
GPT teacher head0.245
Teacher spread0.220 · 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
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
Published2016
Admission routes3
Has abstractyes

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Same venueGlobe Revue internationale d’études québécoisesSame topicCanadian Identity and HistoryFrench-language works237,207