Bibliographic record
Abstract
Justice Rosalie Abella is closely associated with deference to administrative decision makers. I will argue that her deferential approach was multifaceted, much more sophisticated than might typically be assumed. Abella J’s administrative law jurisprudence is as much about administrative autonomy as it is about judicial deference. On one level, Abella J’s jurisprudence is a jurisprudence of judicial restraint, preaching limited judicial oversight of the administrative process. This reflects the conventional way of thinking about deference in administrative law as a doctrine requiring judicial restraint: it is a shield protecting administrative decision makers from judicial interference. Accordingly, she supported a broad presumption of deference to administrative decision makers and articulated a fairly non-interventionist conception of reasonableness review. But, on a deeper level, Abella J’s jurisprudence is more radical. As I explain, Abella J was not committed simply to a restrained approach to judicial review but, rather, to promoting the autonomy of public administration: she furnished swords to administrative decision makers, allowing them to carve out additional space in which to operate and articulate applied versions of legal norms. Her commitment to administrative autonomy, rather than simply to judicial restraint, prompts reflection about the basis of Abella J’s administrative law philosophy, which must ultimately be grounded in her trust of the administrative process, aligning her with the so-called ‘functionalist’ school of thought associated with progressive thinkers. I then turn to the Supreme Court of Canada’s recent rearticulation of Canadian administrative law in the Vavilov case – a rearticulation with which Abella J expressed firm disagreement. I reflect on why the majority and Abella J diverged in Vavilov and suggest that the key features of Abella J’s jurisprudence – restraint and autonomy – are rooted in a mode of thinking about administrative law that has fallen out of favour.
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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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.033 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".