Conacher Missed the Mark on Constitutional Conventions and Fixed Election Dates
Bibliographic record
Abstract
Given the fundamental role that conventions play in the Canadian constitution, it is not surprising that litigants try from time to time to engage the courts in defining or even enforcing the terms of a particular convention. The Federal Court’s September 2009 decision in Conacher v. Canada (Prime Minister)1 is the latest high-profile example. Duff Conacher, Coordinator of Democracy Watch, had launched a court case that challenged the 2008 federal election call as contravening either the provisions of the government’s fixed-date election law (Bill C-16,2 passed in 2007), or conventions supporting the law. The Federal Court rejected Conacher’s application, holding among other things that there was no constitutional convention constraining the prime minister from advising an election before the October 2009 date prescribed in the statute. Conacher’s appeal was also rejected. In May 2010, the Federal Court of Appeal upheld the lower court’s decision, stating that "no such convention exists" based on the evidentiary record.3 For many observers, the Conacher decision may seem unsurprising and solidly based on the existing jurisprudence dealing with constitutional conventions.
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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 | 0.015 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.021 | 0.044 |
| Scholarly communication | 0.013 | 0.016 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.014 | 0.034 |
| Insufficient payload (model declined to judge) | 0.006 | 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".