Bibliographic record
Abstract
Abstract Mark Tushnet has shown great interest in the contrast between weak-form and strong-form judicial review of legislation. In a system of weak-form review, courts scrutinize legislation for its conformity to a Bill of Rights, but courts do not have final power to strike down legislation that is incompatible with the Bill of Rights. They may have power only to issue a Declaration of Incompatibility or they may be constrained, as in Canada, by a “notwithstanding” clause. This chapter examines the domain of weak-form judicial review of legislation. We are familiar with its operation in cases involving possible violations of rights. But constitutional objections to legislation may also be made on structural grounds, such as separation of powers or federalism requirements. Are these instances of judicial review—when they happen—also subject to a weak-form/strong-form distinction? The chapter argues that they are not—that weak-form structural review is more or less unheard of—and it examines the reasons for this discrepancy. Is it because (as Tushnet has argued) rights-based considerations are less determinate? Or is it because structural issues need determinate and timely resolution that weak-form judicial responses cannot provide?
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.015 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| 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".