Bibliographic record
Abstract
Abstract This article examines the conceptual distinction between judicial interpretation and judicial amendment. It argues that there are contexts where courts can depart so far from the constitutional text, the intent or purposes of relevant constitutional provisions, and the broad consensus within the political community about what the constitution does and does not contemplate, that they engage in effective amendment of the constitution. In these instances, judicial reasoning acts in defiance of, or with disregard for, codified constitutional amending procedures. The distinction between judicial amendment and judicial interpretation is not a clear or easy one. An analysis of its invocation in the context of the United States, Canada, and Australia finds that the concept of judicial amendment is often employed in a way that threatens to merely replicate extant debates over competing theories of constitutional interpretation. At a conceptual level then, the distinction between judicial amendment and interpretation requires a high threshold. The article identifies a set of factors to establish when courts are no longer engaged in mere interpretation but are fundamentally altering the constitution itself. It then applies those factors to an analysis of three cases of judicial amendment in Canada and India.
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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.033 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.010 |
| 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".