The Hollowing Out of Corporate Canada: Implications for Transnational Labor Law, Policy and Practice
Bibliographic record
Abstract
In the late 1990s, Jim Atleson and I taught parallel seminars on the effect of globalization on labor law, and arranged for our students—Canadians and Americans—to interact with each other. On one occasion, we set them to negotiating a collective agreement covering the North American auto industry. Students were assigned roles as the leaders or legal advisors of the U.S. and Canadian autoworkers’ unions, and as executives or legal advisors of the American parent companies and their wholly-owned Canadian subsidiaries. We wanted them to comprehend the similarities and differences between the labor laws of our two countries, the difficulties of complying simultaneously with related but noncongruent legal regimes, and the conflicts of laws issues raised by applying domestic labor law to transnational relationships. We also wanted them to understand the problems posed not only by adversarial relations as between management and labor, but by serious divergences of interest and ideology within the ranks of each side. They learned quickly. An e-mail sent by the American management team to its Canadian counterpart accused the latter of not role-playing in accordance with the assump-
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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 | 0.014 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.044 | 0.043 |
| Scholarly communication | 0.019 | 0.010 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.010 | 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".