Punishing “Privilege”: Antisemitic Hate Crime in Canada
Bibliographic record
Abstract
Both federal government and civil society organization data point to consistently rising incidents of antisemitic narratives and acts across Canada. In spite of this, antisemitic hate crime has not been the focus of any academic research here, some would argue because Jews are not typically thought to be an at-risk community. Rather, the Jewish community is thought to occupy a relatively privileged place in society which shields them from bias motivated attacks. Countering this narrative, our study, based in Ontario and Quebec, reveals that Jewish individuals and institutions are highly vulnerable to discursive, physical, and property violations. Many of those we spoke with felt embattled by the narrative attacks that rendered the community vulnerable to corollary physical attacks. Of particular significance are the enabling images of Jews that equate "Jewish privilege" with excessive power and control. We explore these themes, concluding with calls for strategies intended to counter hateful narratives.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".