Beer, Butter, and Barristers: How Canadian Governments Put Cartels before Consumers
Bibliographic record
Abstract
In Canada, various sectors of the economy are subject to government regulations, many of which are designed to correct market failures. However, such regulations are generally inconsistent with federal competition law, which aims to promote economic efficiency by maintaining the integrity of competitive markets. The courts have resolved this tension by developing the Regulated Conduct Defence (RCD) – an interpretive judicial doctrine that immunizes various regulatory regimes from the application of competition law. In this Commentary we challenge the wisdom of the RCD from an economic and legal standpoint. In particular, we criticize the view, established by the courts, that regulations conflicting with competition law should be deemed to operate in the public interest. We argue that certain regulatory regimes advance private interests at an unreasonable cost to consumers. Our analysis includes three examples of regulatory regimes that interfere with competitive forces but nevertheless benefit from immunity to competition law: agricultural supply management, private alcohol retail, and legal services. We propose: (i) clarifying the Competition Act’s application to regulated conduct; (ii) where practicable, limiting the scope of immunity for regulated sectors such that if regulation is deemed necessary, it is narrowly tailored to be minimally impairing to competition; and (iii) requiring the federal government to assess the competitive effects of all legislation prior to enactment.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.059 | 0.031 |
| Scholarly communication | 0.016 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.013 | 0.012 |
| Insufficient payload (model declined to judge) | 0.008 | 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".