National Responsibility and Systemic Racism in Criminal Sentencing: The Case of R. v. Hamilton
Bibliographic record
Abstract
On February 20, 2003, the Ontario (Canada) Superior Court of Justice released R. v. Hamilton, a decision that judicially recognized the impact of systemic racism against the black community in Canada in the sentencing hearing of two Black women who had pleaded guilty to illegally smuggling cocaine into Canada from Jamaica. The judge reduced their sentences based on his view of how systemic racism had impacted their lives and their crimes. In his analysis, the judge followed the legal precedent set by R. v. Gladue (1999) where the Supreme Court reasoned that the demand of section 718.2(e) of the Criminal Code required that Canadian judges who sentence Aboriginal offenders must recognize the historical and systemic disadvantage that First Nations communities have endured and must consider remedial or restorative justice principles in the application of alternative sentencing. In this paper, using R. v. Hamilton, I argue that the application of section 718.2(e) of the Criminal Code of Canada constitutes a practice of nation-building where the negotiation of past injustice in the context of criminal sentencing brings into view how the law produces legitimate citizens and by extension legitimate national history through culturally and racially codifying non-white subjects before the Court. I show how the application of section 718.2(e) in R. v. Hamilton is contingent upon invoking and enacting historical racial narratives, both for the particular subject before the Court (and as a consequence for the racial community to which they belong) and for the Court, as the (moral) arbiter of the nation. These racial narratives I argue, serve a dual function for the project of law and nation-building: they invite the subject before the Court into the universal core values of human rights by circumscribing their claims to personhood along racial and cultural lines and simultaneously, these racial narratives function to inscribe (legal) notions of national responsibility for past injustice. In particular, I suggest that while the application of section 718.2(e) is an instance of anti-racist jurisprudence, its application must be understood through its normative role in establishing the contours of legally codifiable claims to national responsibility as well as its role the production of national subjects.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.038 | 0.015 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.012 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 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".