Bibliographic record
Abstract
Justice Rand's judgment in Roncarelli v Duplessis is rightly reputed to be one of the classic judgments in Canadian public law. Roncarelli is a judgment about administrative law, about judicial review of abuse of administrative discretion. And administrative law - the common law of judicial review - is usually regarded as the lesser part of public law. In contrast, constitutional law, by which is meant the study of the written constitutional texts of a legal order, is considered to be the serious component of public law. This prejudice is deeply positivistic in that it considers that Parliament is subject to constitutional law only when there is a written text which sets out legal controls. Moreover, this text must be entrenched so that judges have the final say over whether statutes offend the constitution unless the constitution is itself changed by a process of amendment beyond the reach of ordinary legislation. At most, constitutional rights are the rights that can be implied into such text, hence the label of "implied bill of rights" for Justice Rand's constitutional judgments, many of which relied on his understanding of the Constitution Act, 1867, and can thus be understood as premised on a constitutional text, even though he found more in the text than had been explicitly stated by its drafters. The common law of judicial review is then not akin to constitutional law, because an omnipotent or supreme legislature - one not subject to a written constitution - can always use legislation as a blunt instrument to override even the boldest common law judge. It is this prejudice that I explore. I argue that judicial review in public law is best understood as based on fundamental constitutional values on a continuum, ranging from the ordinary situations of common law judicial review to the most striking judicial interventions on the basis of an entrenched bill of rights. Just this continuum is revealed by Rand J.'s public law judgments. To see that there is a continuum we must start where it starts--in administrative law - precisely because in administrative law judges have to rely on the idea of the unwritten constitution.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.023 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.016 | 0.025 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".