Through Which Glass Darkly? Constitutional Principle in Legality and Constitutionality Review
Bibliographic record
Abstract
This article seeks to draw lessons from a comparison between the ways in which the Rule of Law is discussed in cases decided by the supreme courts of Canada and the United Kingdom on the issue of allegedly excessive fees levied on litigants seeking to access adjudication. After reviewing the factually quite similar cases of Trial Lawyers Association of British Columbia v British Columbia (Attorney General) and R (Unison) v Lord-Chancellor and it detailing these decisions’ respective constitutional settings, the article argues that, in contrast to the cursory treatment of the Rule of Law by the Supreme Court of Canada, the UK Supreme Court's discussion is sophisticated and instructive. This suggests that legality review based on common law rights, which is not focused, and does not try to establish a connection, however tenuous, to an entrench constitutional text, may well allow for a more forthright and enlightening discussion of the principles at stake. Thus it follows that, in constitutional systems that feature strong-form judicial review based on entrenched texts, when regulations and administrative decisions are at issue, legality review should not be neglected. In those systems where strong-form judicial review is not available, legality review should not be regarded as an anomalous ersatz.
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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 | 0.022 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.070 |
| Scholarly communication | 0.014 | 0.020 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".