Canadian Fundamental Justice and American Due Process: Two Models for a Guarantee of Basic Adjudicative Fairness
Bibliographic record
Abstract
This paper traces how the Supreme Courts of Canada and the United States have each used the basic guarantee of adjudicative fairness in their respective constitutions to effect revolutions in their countries’ criminal justice systems, through two different jurisprudential models for this development. It identifies a relationship between two core constitutional structures, the basic guarantee and enumerated rights, and shows how this relationship can affect the degree to which entrenched constitutional rights actually protect individuals. It explains that the different models for the relationship between the basic guarantee and enumerated rights adopted in Canada and the United States, an “expansive view” and a “narrow view” respectively, changed the degree to which entrenched rights protected individuals. It offers an historical context for these developments, and gives a comparison between a heretofore unexamined parallel in the jurisprudential developments surrounding the basic guarantee in both countries. It then suggests how these different models for the relationship between the fundamental constitutional structures protecting individual rights in the criminal process will respond to the most significant threats to individual rights from the political branches in decades, as a result of the global war on terrorism.
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.013 | 0.021 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".