Grown Close to Home™: Migrant Farmworker (Im)mobilities and Unfreedom on Canadian Family Farms
Bibliographic record
Abstract
Migrant farmworkers in Canada's Seasonal Agricultural Worker Program (SAWP) are bound by unfree labor relations. Migrants are employed by and live adjacent to Canadian family farms. Extending current research on Canada's SAWP, I specifically conceptualize the family farm as a locus of unfree labor relations. The article identifies how employers impose mobility controls around migrants' freedom to leave their workplaces, circumscribing where, how, and when migrants can circulate in Canadian communities. Growers use discourses and practices of paternal care and protection to justify these controls, revealing the familial features of employer–employee relationships. Harnessing a relational understanding of the family farm, I argue that worker (im)mobilities reveal key features of extant family farm relationships. Direct involvement by state officials and legal frameworks undergirding the SAWP effectively enable and sanction employer practices. Contributing to mobilities research, I identify how family farms exercise and directly benefit from state-sanctioned forms of power that allow them to restrict and regulate migrants' mobilities at localized levels. With relevance to both Canadian and U.S. contexts, the power to “fix” farm labor in place is highly desirable for family farms as a labor control mechanism. Material geographies of everyday (im)mobility help employers and states secure high levels of labor control from this low-wage migrant labor force. Arguments are based on qualitative research with fifteen migrant farmworkers employed on ten farms in Norfolk County, Ontario, Canada, as well as additional interviews with sending government officials, local civil society, and growers.
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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 | 0.024 | 0.008 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".