Legislating Statutory Interpretation: The Parliamentary Regulation of Judicial Discretion
Bibliographic record
Abstract
This book seeks to provide insight on a number of important questions related to the theme of legislating statutory interpretation: what motivates or prompts legislative direction to the courts? For instance, does it occur in relation to certain subject matters more than in relation to others? How do courts tend to respond to legislative control of their interpretative discretion? What are the implications of retroactive legislation aimed at “correcting” a past judicial interpretation of a statute? What are the broader issues, such as those relating to the roles of the legislature and judiciary, that are implicated by legislating statutory interpretation? A range of approaches, including those that are comparative, historical and critical, have been deliberately included to provide rich and diverse perspectives on this broader theme. We have organized the contributions into three main sub-themes: (i) case studies and lessons learned; (ii) constitutions, human rights and international law; and (iii) broader reflections on institutional dialogues.
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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 | 0.017 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.048 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| 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".