Interpreting a Bill of Rights: The Importance of Legislative Rights Review
Bibliographic record
Abstract
This article contests the widely held view that an effective bill of rights requires judicial interpretation of rights to prevail over political judgement. Most bills of rights reflect classical liberal assumptions that premise freedom and liberty on the absence of state intervention. Yet they govern modern welfare states that presume and require substantial state involvement, seen to various degrees as facilitating rather than restricting the conditions for robust and equal citizenship. Judges cannot provide answers that are so definitive or persuasive to questions about whether social policy is reasonable in terms of human rights that they rule out other reasonable judgements. Although these concerns are often used to justify rejecting a bill of rights, this article takes a different position. It argues that a political community can benefit from exposure to judicial opinions on whether legislation is consistent with rights, but should also encourage and expect parliament to engage in legislative rights review. The article discusses how three parliamentary systems have attempted to infuse more concern for rights in their processes of decision making, and concludes with suggestions on how legislative rights review can be strengthened.
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 | 0.200 | 0.314 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.011 | 0.051 |
| Scholarly communication | 0.025 | 0.029 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.024 | 0.025 |
| Insufficient payload (model declined to judge) | 0.003 | 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".