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Record W4402449737 · doi:10.33137/wij.v20i1.43967

New Challenges, Old Hatred: The Role of Super-diversity, Immigration, and Political Polarization in the Rise of Antisemitism in Contemporary Canada

2024· article· en· W4402449737 on OpenAlexaffvenueabout
Megan Hollinger

Bibliographic record

VenueWomen in Judaism A Multidisciplinary e-Journal · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicJewish Identity and Society
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAntisemitismHatredImmigrationPoliticsPolitical sciencePolarization (electrochemistry)Diversity (politics)EthnologyPolitical economyHistorySociologyJudaismLawArchaeology

Abstract

fetched live from OpenAlex

This paper examines the rise of antisemitism in contemporary Canada and explores some emerging social trends that may exacerbate and enable it. Specifically, the rise and maintenance of antisemitism in Canada may be, in part, due to the multifaceted diversification of the West known as super-diversity, as well as increasing political polarization. By examining super-diversity and its implications, this paper explores the connections between immigration and diversification, the growth of political polarization, and the rise in antisemitism across Canada. This paper argues how the aforementioned social trends may lead to the existence of more antisemitic manifestations and motivations in Canada. Of particular concern is the importation of certain anti-Israel and anti-Zionist biases found within populations arriving in Canada and coming from parts of the world where tensions with Israel are present. Additionally, political polarization heightens intergroup tensions in Canada and may foster a broader atmosphere of prejudice.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score0.602

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.272
Teacher spread0.251 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2024
Admission routes3
Has abstractyes

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