Trouble in our Fields: Health and Human Rights among Mexican and Caribbean Migrant Farm Workers in Canada
Bibliographic record
Abstract
For many years Canada has quietly rationalized importing temporary “low-skilled” migrant labour through managed migration programs to appease industries desiring cheap and flexible labour while avoiding extending citizenship rights to the workers. In an era of international human rights and global competitive markets, the Canadian Seasonal Agricultural Workers Program (SAWP) is often hailed as a “model” and “win-win” solution to migration and labour dilemmas, providing employers with a healthy, just-in-time labour force and workers with various protections such as local labour standards, health care, and compensation. Tracing migrant workers’ lives between Jamaica, Mexico and Canada (with a focus on Ontario’s Niagara Region), this thesis assesses how their structural vulnerability as non-citizens effectively excludes them from many of the rights and norms otherwise expected in Canada. It analyzes how these exclusions are rationalized as permanent “exceptions” to the normal legal, social and political order, and how these infringements affect workers’ lives, rights, and health. Employing critical medical anthropology, workers’ health concerns are used as a lens through which to understand and explore the deeper “pathologies of power” and moral contradictions which underlie this system. Particular areas of focus include workers’ occupational, sexual and reproductive, and mental and emotional health, as well as an assessment of their access to health care and compensation in Canada, Mexico and Jamaica. Working amidst perilous and demanding conditions, in communities where they remain socially and politically excluded, migrant workers in practice remain largely unprotected and their entitlements hard to secure, an enduring indictment of their exclusion from Canada’s “imagined community.” Yet the dynamics of this equation may be changing in light of the recent rise in social and political movements, in which citizenship and related rights have become subject to contestation and redefinition. In analyzing the various dynamics which underlie transnational migration, limit or extend migrants’ rights, and influence the health of migrants across borders, this thesis explores crucial relationships between these themes. Further work is needed to measure these ongoing changes, and to address the myriad health concerns of migrants as they live and work across national borders.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.032 | 0.010 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".