A Gesture of Criminal Law: Jews and the Criminalization of Hate Speech in Canada
Bibliographic record
Abstract
In June 2020, the fiftieth anniversary of the criminalization of hate speech in Canada passed with little notice. Since their enactment in 1970, the hate-speech provisions in the Criminal Code have seldomly been enforced. They are commonly viewed as ineffective. In light of this half-century of experience, it is beneficial to re-examine the history of the criminalization of hate speech for lessons this story may hold. This article does so by exploring the genesis of the legislation from the perspective of the Canadian Jewish community. It focuses on the Jewish community because Canadian Jewry—especially the Canadian Jewish Congress—was the primary driver behind the bill. Accordingly, a focus on the Jewish community is essential to understanding why hate speech was criminalized, how the language of the provisions was decided upon, and why they are infrequently invoked. Commentators have acknowledged Jewish efforts, but the singular contribution of Canada’s Jews has not received full attention. This article fills this gap. Relying extensively on archival research and oral history, this article’s central claim is that the main goal of the legislation was not to prosecute hatemongers. Rather, its purpose was predominantly symbolic: to enshrine equality principles in the criminal law and to send the message that Canada was a multicultural and tolerant society. In fact, Congress leadership long resisted this type of legislation and came to support a group libel provision only under intense pressure from its community grassroots, especially Holocaust survivors, who demanded a forceful response to rising neo-Nazism. However, Congress and other advocates of the bill were focused on the symbolism of getting the legislation passed and were unconcerned with how it would later be used. In doing so, they ignored the vigorous protests of Holocaust survivors who accurately predicted that the law would be difficult to implement. At bottom, this is a tale of the risks and potential benefits of the symbolic use of the criminal law.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.053 | 0.017 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".