Bibliographic record
Abstract
This dissertation explores the political economy of the physical and mental illnesses that the migrant workers experience while living and working under conditions of illegality in Canada's late capitalism.The dissertation is divided into three parts.The first part locates four social determinants of health underpinning the structural vulnerability to which the Latin American undocumented workers are subjected in this particular context.Based on the data gathered on the ground, this part shows that, for this particular population, the condition of being "subjects of administration," "subjects of deportability," "subjects of racialization" and "subjects of exploitation," work as primary sources of physical and mental illnesses.The completion of my doctoral studies, and of this dissertation, in particular, were possible because of the support I received from an important number of people, organizations, and institutions to whom I want to express my gratitude.First of all, I want to thank all the workers who trusted me, shared their time and stories with me, and provided me with ideas throughout the research process.Among them, I learned that when one lives in a context of deep precarity and engaged in a daily struggle to survive deportability, alienation, suffering, and exploitation, it is very difficult to trust in others.Despite this, the workers I interviewed generously overcome mistrust and patiently spent part of their valuable time telling me their stories.Their participation made the very existence of this work possible.Gracias, de veras.Alma, Raquel, Laura, Raul, Robert, Alejandra, and my compadres Toño and José, were particularly generous throughout the research process.They do not only provided me with housing and mealtime company, but also encouraged me to get things done when I was low
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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 | 0.002 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.003 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".