The meta-constitution: amendment, recognition, and the continuing puzzle of supreme law in Canada
Bibliographic record
Abstract
This paper uses the idea of the meta-constitution to interrogate issues with Canada’s constitutional amendment and recognition procedures. Put simply, the meta-constitution is that part or parts of a written constitution which are self-referential. Typically, meta-constitutions explain what document(s) make up the constitution and how the constitution can be amended. Most meta-constitutions are simple but Canada’s is not and the difficulties with Canada’s meta-constitution highlight the key legal and political role that this often overlooked constitutional feature plays. In 2014, the Supreme Court of Canada issued decisions in two reference cases which dealt with meta-constitutional issues and, as argued in this paper, the Court used the meta-constitution to greatly expand the scope of what courts regard as supreme law in Canada.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.026 | 0.029 |
| Scholarly communication | 0.017 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 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".