Liberte, Egalite, Argent: Third Party Election Spending and the Charter
Bibliographic record
Abstract
Both the federal government and the courts have brought about changes in election law. The author reviews these recent changes In the legal landscape that surround election rules, in particular third party election spending. The questions of what rules exist" and "who shall make them" are particularly important to the discussion as this area of law tries to reconcile individual interests in liberty and equality in a democracy. The trio of Supreme Court of Canada decisions. Libman v. Quebec (A.G.), Thomson Newspapers v. Canada (A.G.) and Sauvi v. Canada (Chief Electoral Officer), reveal ambiguity in the Court's rationale for limiting individual liberty at election time. This ambiguity is broached in the recent Supreme Court of Canada case of Harper v. Canada (A.G.) where the Court accepted that Parliament may legitimately seek to create a "level playing field" at election time.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".