Transforming Structures of Violence: How Gender-Based Violence Impacts Temporary Foreign Workers in Canada's Agricultural Sector
Bibliographic record
Abstract
The Temporary Foreign Worker Program (TFWP) is a critical source of labour for Canada’s agricultural sector. Temporary foreign workers (TFW) are vulnerable for a variety of reasons including structural inequities, lack of status, and limited individual rights. Compounding this are the diverse identities of individual workers, including gender, sexual orientation, age, race, ethnicity, marital status, religion, disability, Indigenous identity, languages spoken, and/or geographic location. This scoping review aims to understand how the TFWP contributes to, interacts with, and addresses gender-based violence (GBV) from both a conceptual and real viewpoint. Key research objectives include: Collect documented evidence (articles, reports, policies) regarding GBV and TFWs in the agricultural sector. Describe how GBV is experienced differently by diverse groups of TFWs in Ontario, Quebec and British Columbia.Understand how policies (municipal, provincial, federal) address or confront GBV experienced by TFWs in these three provinces.Outline which infrastructure (social, physical, and other) exists to support TFWs and how supports can be enhanced to better support TFWs who experience GBV. Emphasis will be placed on the different experiences of GBV within these systems and infrastructures. Supporting the above objectives, we will identify roles and tailored knowledge mobilization materials specific to academic, public, private, and not-for-profit sectors. This will include policy recommendations, best practices, and tools for each respective stakeholder group. The results of the research will be shared with key stakeholders through a knowledge mobilization strategy that aims to engage audiences with the results and potential recommendation they might apply in their work.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".