The Administration of Justice: Justice Rosalie Abella’s Contribution to Canadian Administrative Law
Bibliographic record
Abstract
Over the course of her impressive legal career, Justice Rosalie Abella has been a champion for the administration of justice – a constitutional paradigm in which the legislative, executive, and judicial branches of government all share a fundamental duty to ensure that constitutional principles and values are sustained in practice. Thus, she has repeatedly urged judges to exercise restraint when assessing the legality of administrative decisions because administrative officials have valuable experience and expertise regarding the purposive interpretation of legislation. Understanding this constitutional paradigm helps one to identify unifying themes in Abella J’s administrative law jurisprudence and draw important connections between her work and other leading Canadian jurists like Justices Ivan Rand and Bora Laskin. Moreover, it helps one to distinguish this constitutional paradigm from another formalistic constitutional perspective that perceives the judicial role primarily in terms of maintaining an institutional hierarchy in which judges have an interpretive monopoly to determine the content of the law. While the tension between these two constitutional paradigms is apparent in Canada (Minister of Citizenship and Immigration) v Vavilov, Abella J’s work provides important insights on how to grapple with this tension in a productive and principled manner.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.056 | 0.028 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.007 | 0.013 |
| 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".