Bibliographic record
Abstract
This article analyses the Canadian constitutional case-law in which the Supreme Court uses the doctrine of deference, and considers the justifications for this doctrine. The two main justifications that have been advanced for deference concern the judiciary's alleged institutional incompetence and the lack of democratic legitimacy. I argue that none of these arguments can explain the doctrine of deference as developed and used by the Supreme Court of Canada. It will be shown that courts are perfectly capable of making decisions on constitutional questions. And as for democratic legitimacy arguments - which are based on the fear of subjective reasoning - they are seriously undermined by the indeterminate and subjective application of the doctrine. In fact, it will be shown that deference only adds subjectivity to the analysis. This is what I will call the paradox of judicial deference. It will further be argued that a relaxed level of constitutional review is indeed justified only when the risk of a judicial mistake is too high for us as a society to take. And in such cases, rather than using the vague concept of deference, a relaxed but explicit test must be developed.
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 | 0.008 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.021 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".