A Federal Anti-Scab Law for Canada? The Debate Over Bill C-257
Bibliographic record
Abstract
“...there is a long tradition in Canada of labour legislation and policy designed for the promotion of the common well-being through the encouragement of free collective bargaining and the constructive settlement of disputes.”- Preamble to the Canada Labour Code here is a scene in the film Billy Elliot of replacement miners being bused in to work in Northern England while the striking workers pelt them with eggs and insults. The striking miners tell the replacement workers that they might as well be stealing the food they needed to feed their families. While images like these are rare in Canada today, picket line confrontations are no less tense. The fact that most businesses in Canada are allowed to hire people to do the jobs of striking workers is still very contentious among interested parties. This article reviews the arguments for and against adopting an anti-scab law and considers what impact such laws have on unions, businesses and individual workers. This article will then look at the constellation of players in today’s debate: governments, political parties, labour organizations, and the business community. The article will focus on the Canadian Labour
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.028 | 0.011 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.017 | 0.013 |
| Insufficient payload (model declined to judge) | 0.011 | 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".