Bibliographic record
Abstract
The production of fruit, vegetables, and other horticultural crops in Canada relies upon the embodied labour of migrant agricultural workers who plant, prune, and harvest these crops. Using a feminist geopolitical lens, I foreground the bodies of these workers as these bodies are situated at the intersection of everyday lived experiences and systems of capitalist production through, in this case, Canada’s Seasonal Agricultural Worker Program (SAWP). Drawing on workers’ experiences of their bodies in the context of the regulatory provisions of the SAWP, I highlight the contradictory disembodiment of agricultural workers at the same time that their bodies are necessary to provide the physical labour at the heart of fruit and vegetable production. The disembodiment of these workers is possible because of their status as racialized non-citizens: while Canadians can insist upon the recognition of their bodies, migrant agricultural workers cannot. The disjuncture between embodied labour and embodied subjectivities was exacerbated with the onset of the COVID-19 pandemic, which disproportionately affected on migrant agricultural workers – through their bodies – while in Canada. Given the relative safety afforded to those who held citizenship (and other permanent) status in Canada, I argue that the active disembodiment of migrant agricultural workers in Canada demonstrates the ways that embodiment is a privilege that is tightly bound to citizenship.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.312 | 0.074 |
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".