Bibliographic record
Abstract
Constitutional amendment ordinarily channels public deliberation through formal, transparent, and predictable procedures designed to express the informed aggregated choices of political, popular, and institutional actors. Yet the Government of Canada’s proposed senator selection reforms concealed a democratically problematic strategy to innovate an informal, obscure, and irregular method of constitutional change: constitutional amendment by stealth. There are three distinguishing features of constitutional amendment by stealth—distinctions that make stealth amendment stand apart from other types of informal constitutional change: the circumvention of formal amendment rules, the intentional creation of a convention, and the twinned consequences of both promoting and weakening democracy. Constitutional amendment by stealth occurs where political actors consciously establish a new democratic practice whose repetition is intended to compel their successors into compliance. Over time, this practice matures into an unwritten constitutional convention, and consequently becomes informally entrenched in the constitution, though without the democratic legitimacy we commonly associate with an amendment. In this article, I theorize constitutional amendment by stealth from legal, theoretical, and comparative perspectives, and consider its consequences for the rule of law.
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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.031 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".