To Bite the Hands that Feed : Control and Competition in Temporary Foreign Worker Programs amidst a Pandemic
Bibliographic record
Abstract
Canada’s continuous reliance on temporary foreign workers to address its labour shortage and maintain its competitive advantage has resulted in a seasonal transnational workforce characterized by its precarious living and working conditions, cumulative legal disenfranchisement based on the lack of permanent status, and vulnerability to the ongoing pandemic. Despite the common portrayal of the Seasonal Agricultural Worker Program (SAWP) as a ‘model for migration management’ by governments and growers, a large body of academic publications has studied their precarious conditions in an attempt to explain the seeming contradiction between a highly-exploited workforce and the steady growth of willing participants. This project examines the exploitative practices embedded in the cycles of transmigration through a series of individual interviews with SAWP participants, scholars, and government officials. The central argument is that the differential treatment of migrant and citizen workers lies at the heart of the former’s precarity. It stems from the paradoxical promotion of human rights at the macro-level, while relying on an exploited workforce at the micro-level. The program creates mechanisms that keep workers in a state of continuous marginalization despite decades of participation in the program. The legal, subtle, and overt mechanisms that maintain workers in a continuous state of control and competition are among the key findings of this project. This project challenges the idealization of the SAWP by analyzing the main beneficiaries, its shortcomings, and its projected future. It presents a unique opportunity to reimagine temporary foreign worker programs and methodological nationalism in a globalized context.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".