Housing, health equity, and global capitalist power: Migrant farmworkers in Canada
Bibliographic record
Abstract
Health scholars are becoming increasingly attuned to the intimate ties between a person's housing and their access to mental and physical health. However, existing models for understanding the link between housing and health equity do not adequately theorize why inequities arise and persist, who benefits from these social arrangements, and how they operate transnationally. How do domestic and global dynamics of political economy shape housing and health equity for migrant farmworkers? How can conceptual models of housing and health equity better account for political economy? To answer these conceptual questions, our study examines the empirical case of migrant agricultural workers in Canada. Migrant worker housing provides a pertinent case for better conceptualizing capitalist power dynamics in housing and health equity on a global scale. Specifically, we draw on in-depth interviews conducted between 2021 and 2022 with 151 migrant workers Ontario and British Columbia. Participants' housing and health concerns aligned with existing literature, including issues such as overcrowding and barriers to health care due to a remote rural location. Our analysis identified three empirical themes: Precarity, Paternalism, and a lack of Political Participation. Drawing from these insights, we recommend a refined model of housing and health equity that keeps an analytical lens trained on global racial capitalism.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".