The Societal Impact of Punishment Theories in Canada's Offender Sentencing Practices
Bibliographic record
Abstract
There has been controversy surrounding high-profile Canadian court cases due to stakeholders asserting that justice was not delivered in the offenders’ sentencing. Cases such as R v. Bernardo (including R. v. Homolka), R v. Pickton and R v. Li have drawn criticism from stakeholders, such as the victims’ families and the public, for perceived lax and disproportionate sentencing. I aim to make sense of and determine why this is their perception of these cases and offer a way to understand these cases’ judicial decisions. Reading these cases through the lens of philosophical punishment theories will (1) determine the underlying compatible legal theory guiding these sentences that are perceived as lax and disproportionate, (2) explain the reasoning behind these sentences, and (3) help us understand why the public and the victims’ families perceive these sentences as lax and disproportionate. In this thesis, I will argue that Canada’s criminal justice system could be understood as incorporating various punishment theories for criminal offender sentencing, such as strict retribution, utilitarianism, and paternalism as a form of rehabilitation. I will focus my research on three punishment theories that I believe have been significant in guiding the law’s application in the Canadian legal system and the modern history of Western law: Immanuel Kant’s strict retributive punishment theory, Jeremy Bentham’s utilitarian punishment theory, and Herbert Morris’ paternalistic punishment theory. I will argue that by identifying the underlying punishment theories, we can identify where the judicial decision is perceived as flawed by the public and the victims’ families and how to understand the effect of these theories in future judicial decisions. Based on my findings, I will sketch an alternative Kantian punishment theory that can be a theoretical lens through which we can evaluate proportionality in sentencing by providing a victim-centred approach to punishment.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.037 | 0.018 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".