Criminal Justice, Democratic Fairness, and Cultural Pluralism: The Case of Aboriginal Peoples in Canada
Bibliographic record
Abstract
From the outset, then, this plurality of motivations behind criminal justice and punishment render the relationship between democracy and punishment complex.But the picture soon becomes more complicated when we consider that punishment is the last stage in the criminal justice process.Before a person can be lawfully punished, he or she must have gone through a legally defined procedure to determine guilt.And before that procedure can take place, of course, there must have been legislation to define both criminal procedure and the substance of criminal law.Each of these three functions of a criminal justice system-the definition of criminal wrongdoing, the prescribed process for determining guilt or innocence, and the definition and enforcement of sanctions for criminal misconduct-is potentially available for assessment according to standards of democratic fairness and accountability.2 More specifically, the democratic principle of equality can serve as a standard for evaluating each of these functions: Do definitions of criminal behavior effectively discriminate against particular classes of citizens?Are procedures to determine an accused person's guilt or innocence equally applied, and equally appropriate, to all citizens?Are punishments meted out even-handedly primary purpose of incarceration; 20 percent believe that punishment is its purpose, and 10 percent believe that deterrence is its purpose.American Civil Liberties Union, New Poll Shows Surprisingly Forgiving Attitude Toward Crime and Punishment: Most Americans Don't Want to Throw Away the Key, available at http://www.aclu.org/news/2001/n071901a.html (July 19, 2001) Disagreement over the purpose of punishment is not only a phenomenon among members of the mass public.In issuing their sentencing guidelines, the seven members of the United States Sentencing Commission had to avoid addressing the principled bases for different sentences, since they did not agree on the principles.Instead, they reached agreement on specific sentences and left it at that.Cass Sunstein cites this as an example of an "incompletely theorized agreement" that is nonetheless legitimate.Designing Democracy: What Constitutions Do 53-54 (2001).2. For a discussion of these three functions of criminal law in relation to Aboriginal peoples in Canada, see Royal Commission on Aboriginal Peoples, Bridging the Cultural Divide: A Report on Aboriginal People and Criminal Justice in Canada 234-35 (1996) (citing H.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.064 | 0.010 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| 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".