Bibliographic record
Abstract
Judicial review of legislation to ensure its compatibility with vague and abstract principles of political morality is often argued to be incompatible with the democratic right of ordinary citizens to participate on equal terms in public decision making. Adrienne Stone argues that ‘structural’ judicial review, aimed at protecting constitutional structures such as federalism and the separation of powers, is just as vulnerable to this objection as ‘rights’ review, aimed at protecting constitutionally entrenched rights. I argue that some kinds of structural review are distinguishable from rights review and not susceptible to the objection: it does not apply to (a) judicial enforcement of provisions dividing powers within a federation; (b) genuine ‘manner and form’ requirements governing the composition, powers, and procedures of the legislature and its houses, provided that they leave its substantive power to legislate unaffected; (c) a requirement that only independent courts may exercise the judicial power of determining the concrete legal rights and duties of litigants, based on the application of general laws that legislatures have made and remain free to change; or (d) provisions forbidding states or provinces within a federation from discriminating against the residents or commercial enterprises of other states or provinces.
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 | 0.078 | 0.165 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.041 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.019 | 0.016 |
| 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".