Disarming Canadians, and Arming them with Tolerance: Banning Firearms and Minimum Sentences to Control Violent Crime--An Essay on an Apparent Contradiction
Bibliographic record
Abstract
In an article published in French in 1997, the author offered reflections on feminism and criminal law that would allow for a better control of violent crime, without Parliament having to resort to excessively severe sentences. In this respect, she argued that there was no contradiction in supporting the radical ban of firearms in Canada, while opposing a minimum sentence of four years under the Firearms Act, which currently affects approximately ten serious Criminal Code offences. After setting out her position in favour of the "disarmament" of Canadians, the author argued that minimum sentences of four years were unconstitutional. Such sentences would constitute cruel and unusual punishment under section 12 of the Charter. They would also be contrary to one of the principles of fundamental justice guaranteed under section 7, which mandates proportionality between offences and sentences. Finally, the author argued that minimum mandatory sentences could not fulfill the objectives of general deterrence and of deserved retribution. On the contrary, they are ineffective in helping to reduce violent crime, and lead to arbitrary applications. In her epilogue to her 1997 article the author expresses her regret that the principle of proportionality has not been promoted as a constitutional principle of justice in the Momsey and the Latimer cases, and wonders if times are too hard for tolerance and moderate sentencing.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.023 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".