Issue 02: Key Issues & Recommendations for Canadaâs Temporary Foreign Worker Program: Reducing Vulnerabilities & Protecting Rights
Bibliographic record
Abstract
In this issue of Policy Points we have identified some of the most significant rights issues facing Temporary Foreign Workers (TFWs) in Canada based on our empirical research amassed over a decade of study. In order to address these problems, we have provided a number of recommendations for the Temporary Foreign Worker Program (TFWP) with an emphasis on some of the most vulnerable workers – those in the Pilot Project for Occupations Requiring Lower Levels of Formal Training (NOC C & D Pilot), and the Seasonal Agricultural Worker Program (SAWP). While recognizing that there are jurisdictional differences and many other changes could be integrated at the provincial and municipal levels, the following provide the most essential federal-level recommendations.
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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 | 0.025 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.022 | 0.011 |
| Scholarly communication | 0.020 | 0.010 |
| Open science | 0.010 | 0.005 |
| Research integrity | 0.044 | 0.026 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".