Harvest Histories: A Social History of Mexican Farm Labour in Canada since 1974
Bibliographic record
Abstract
While concerns and debates about an increased presence of non-citizen guest workers in agriculture in Canada have only more recently begun to enter the public arena, this dissertation probes how migrant agricultural workers have occupied a longer and more complex place in Canadian history than most Canadians may approximate.It explores the historical precedents of seasonal farm labour in Canada through the lens of the interior or the personal on the one hand, through an oral history approach, and the external or the structural on the other, in dialogue with existing scholarship and through a critical assessment of the archive.Specifically, it considers the evolution of seasonal farm work in Manitoba and British Columbia, and traces the eventual rise of an "offshore" labour scheme as a dominant model for agriculture at a national scale.Taking 1974 as a point of departure for the study of circular farm labour migration between Mexico and Canada, the study revisits questions surrounding Canadian views of what constitutes the ideal or injurious migrant worker, to ask critical questions about how managed farm labour migration schemes evolved in Canadian history.In addition, the dissertation explores how Mexican farm workers' migration to Canada since 1974 formed a part of a wider and extended world of Mexican migration, and seeks to record and celebrate Mexican contributions to modern Canadian agriculture in historical contexts involving diverse actors.In exploring the contexts that have driven Mexican out-migration and transnational integration, it bridges oral accounts with a broader history that sets Mexican northward migration in hemispheric context.It reads agricultural migration upon various planes, including corporeality, experience, identity, masculinity, legality, "contra-modernity," and the management of mobilities.
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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 | 0.003 | 0.007 |
| Science and technology studies | 0.029 | 0.008 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".