Retribution Versus Rehabilitation: Why North America should Adopt the Nordic Prison Model
Bibliographic record
Abstract
Both Canada and the United States of America have a considerable imprisonment issue, leading to calls for prison reforms. When considering the role of punishment in the legal system, research indicates that individuals tend to want to achieve three objectives: retribution, general deterrence, or specific deterrence. The Nordic Prison Model, which focuses on rehabilitating the individual, may be a solution to the current North American retribution-oriented penal system. In this position paper, I will examine the contentious issues plaguing the current North American prison system, research around the role punishment plays in society, arguments against rehabilitation and the Nordic system, and finally, the growing evidence advocating for a paradigm shift toward adopting a rehabilitative-oriented remand system. Lastly, the paper ends with a call to action on future research into the feasibility of enacting a rehabilitative-oriented prison model in capitalist countries such as the USA and Canada, as well as policy implications including increasing educational courses or work-release programs.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".