Migrant workers and fissured workforces: CS Wind and the dilemmas of organizing intra-company transfers in Canada
Bibliographic record
Abstract
Canadian temporary foreign worker programs have been proliferating in recent years. While much attention has deservedly focused on programs that target so-called low-skilled workers, such as seasonal agricultural workers and live-in caregivers, other programs have been expanding, and have recently been reorganized into the International Mobility Program (IMP). Streams within the IMP are quite diverse and there are few legal limits on their growth. One of these, intra-company transfers (ICTs), is not new, but it now extends beyond professional and managerial workers to more permeable and expansive categories. As a result, unions increasingly face the prospect of organizing workplaces where ICTs and other migrant workers are employed alongside permanent employees, raising difficult legal issues and strategic dilemmas. This article presents a detailed case study of one union’s response to this situation.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.060 | 0.016 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".