Bibliographic record
Abstract
This chapter examines the power of the legislature to have ’the last word’ under section 33 of the Canadian Charter of Rights, and the UK Human Rights Act 1998. In both cases, the democratically elected legislature is empowered to legislate notwithstanding rights. Whilst both of these provisions have been hailed as the lynchpin of a New Commonwealth model of constitutionalism, or as an instance of weak-form review, this chapter observes that they have hardly ever been used. The task of the chapter, then, is to examine and explain ’the underuse of the override’. Departing from the dominant narrative that the legislature wanted to use the override but was thwarted by exogenous political costs, this chapter argues that the rare use of the override was part of the original design of both systems from the outset. Instead of being a tragic thwarting of democratic dialogue, or an unfortunate atrophy of constitutional powers, rare use of the override was a feature, not a bug in both systems. Supplementing the historical narrative with normative argument, the chapter defends the rare use of the override as a vindication of the collaborative constitutional ideal.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.023 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".