Constructing the Modern Hacienda: Land, Work, Memory and Migration in the Seasonal Agricultural Worker Program
Bibliographic record
Abstract
This dissertation examines the everyday lives of Mexican migrants participating in the Seasonal Agricultural Worker Program (SAWP). I examine the SAWP as an example of how the Canadian state mobilizes neoliberal governance techniques to decentralize power and court political support, while also establishing labour stratification according to immigration status, race, and occupational sector. I use migrants’ experiences in this context to critically examine neoliberal interventions as they affect power relations, land, development, and work. I am particularly interested in interrogating the effectiveness of these interventions as well as investigating what forms of resistance, control, and discipline are possible as they become vernacularized within local power relations. To do this, I draw on 14 months of fieldwork conducted between 2012 and 2014 in both Canada and Mexico. My fieldwork was multi-sited and included working on Meadowvale Farms, a medium-sized vegetable farm in Southern Ontario, as well as living in the Central Mexican village of Atzala. The first portion of this dissertation examines how migrants are constructed as a productive and manageable workforce. I argue that examinations of the structural and historical factors contributing to migrants’ exploitation only provide a partial understanding of this process. It is often in the “offstage” life of the farm, conducted in intimate spaces such as bunkhouses and working spaces, that these factors are both reproduced and challenged. The latter portion of the dissertation is based on fieldwork conducted in Mexico and focuses on the themes of rural development programs, land tenure, and resistance as they relate to the lives of SAWP migrants. I argue that neoliberal state-making has fundamentally changed the role of land and work in rural Mexico and that these shifts have created an increasingly competitive environment that has often excluded SAWP migrants. However, these changes also have limited and often contradictory affects in local communities such as Atzala. My central argument is that SAWP migrants negotiate these interventions and changes through using moments of impasse to explore novel ways of resisting and refusing attempts to coopt their participation in acts of self-discipline and conformity.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".