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<i>Kanada? The Canadian Jewish News</i>and the Memory of the Holocaust in Canada

2013· article· en· W2293839937 on OpenAlexaboutno aff
Magdalena Kubów

Bibliographic record

VenueHolocaust Studies · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsThe HolocaustJudaismImmigrationLegislationNazismPolitical sciencePsychological nativismLawSociologyCriminologyMedia studiesHistoryPoliticsArchaeology

Abstract

fetched live from OpenAlex

After the Second World War, Canada remained inaccessible to European victims of Nazism and made clear its position that the issue of survivors ‘was not Canada’s problem’. Nevertheless, after extensive lobbying by the Canadian Jewish Congress (CJC) and other groups, Canada’s immigration policies began to ease, resulting in the greatest influx of Jewish immigrants to the country since 1911. Although the initial impact of the survivors was limited, The Canadian Jewish News (CJN) – the most influential vehicle for expressing the concerns of the Canadian Jewish community – created an awareness of the Holocaust’s long-term implications on Canadian and international Jewry by easing strained relations and bridging the gap between the established and survivor communities. If not for the pioneering achievement of the CJN and the Holocaust survivors who politicised important issues and made them resonate with the wider public, Canada’s memory and recognition of the Holocaust, legislation on hate crime, and school curriculum would be lacking.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.094
Threshold uncertainty score0.679

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0340.012
Scholarly communication0.0100.003
Open science0.0010.002
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0090.001

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 head0.017
GPT teacher head0.218
Teacher spread0.201 · 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 designQualitative
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

Citations1
Published2013
Admission routes1
Has abstractyes

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