Citizenship at the Margins: The Canadian Seasonal Agricultural Worker Program and Civil Society Advocacy
Bibliographic record
Abstract
This article evaluates the role civil society organizations play in helping noncitizen migrant workers access to social rights in Canada. The study focuses on the bilateral Canadian Seasonal Agricultural Workers Program, a temporary worker scheme that brings Mexicans to Canada to work as harvesters for a four‐to‐eight‐month period. Despite the common description of this program as “best practice,” questions are raised about the ability of workers to access citizenship rights and even limited labor protections. We draw on primary field research conducted in the province of Ontario's agricultural sector to consider how involvement of civil society state actors operating at a variety of scales—local, national, international, and the extra territorial—in a range of social justice struggles expands access to social citizenship rights for Mexican migrant workers. Este artículo evalúa el rol que juegan las organizaciones de la sociedad civil en la ayuda a los trabajadores migrantes no‐ciudadanos en el acceso a derechos sociales en Canadá. El estudio se enfoca en el Programa Bilateral Canadiense de Trabajadores Agrícolas Temporales (SAWP, por sus siglas en inglés), un esquema de trabajo temporal que lleva mexicanos a Canadá a trabajar como segadores por un periodo de entre cuatro y ocho meses. A pesar de la descripción de este programa como de una “buena política/práctica,” surgen preguntas acerca de la habilidad de los trabajadores de acceder a derechos ciudadanos y hasta de protección laboral limitada. Analizamos a partir de una investigación primaria conducida en el sector agrícola de la provincia de Ontario, considerar cómo la participación de actores estatales de la sociedad civil en una variedad de niveles—local, nacional, internacional y extraterritorial—en el ámbito de la justicia social amplía el acceso de los trabajadores migrantres mexicanos a los derechos sociales.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.007 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.006 |
| 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".