Local Produce, Foreign Labor: Labor Mobility Programs and Global Trade Competitiveness in Canada*
Bibliographic record
Abstract
A bstract Temporary visa workers are increasingly taking on a heightened profile in Canada, entering the workforce each year in greater numbers than immigrant workers with labor mobility rights (Sharma 2006). This paper examines the incorporation of foreign workers in Canadian horticulture under the Seasonal Agricultural Workers Program (SAWP). I argue that foreign labor supplied under the SAWP secures a flexible workforce for employers and thus improves Canada's trade competitiveness in the global agrifood market. Using multiple research strategies, I track the evolution of Canadian horticulture in the global market and the transformation of labor in this industry. I outline the steady growth in the employment of temporary visa workers in the horticultural industry and show how they have become the preferred and, in some cases, core workforce for horticulture operations. The benefits of SAWP workers to employers include the provision of a workforce with limited rights relative to domestic workers and considerable administrative support in selecting, dispatching, and disciplining workers provided at no cost by labor supply countries. I conclude that the SAWP is a noteworthy example of the role of immigration policy in regulating the labor markets of high‐income economies and thus ensuring the position of labor‐receiving states within the global political economy.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".