Policy Reform Advocacy for the Healthcare Rights of Critically Ill International Agricultural Workers
Bibliographic record
Abstract
International agricultural workers (IAWs) are vital to Canada's agricultural sector and economy, yet their healthcare rights remain precarious. Despite contributing to health insurance during their employment, many IAWs lose access to healthcare when they become critically ill due to systemic barriers. The problem lies in the lack of clarity over jurisdiction: IAWs are brought in through a federal program, but healthcare delivery falls under provincial authority. This gap underscores an urgent need for policy reform to guarantee continuity of healthcare access for IAWs. Our project advocates for a policy that provides critically ill IAWs access to their insurance. Using the EPIC method, we contacted eight government officials, engaging six in meaningful discussions, with one committing to support our proposed policy. These involved officials whose party was familiar with our agenda but also those who were not. We presented our proposal that indicated how providing healthcare would not financially strain Canada's healthcare system. Furthermore, ensuring healthcare access for IAWs aligns with Canada's core values of equity and compassion. These efforts were supported by collaborations with community leaders to gain insights into the lived experiences of IAWs and to broaden our support network. Due to the nature of advocacy, this process remains ongoing until the goal of policy change has been achieved. This work underscores the importance of structured, empathetic advocacy in addressing systemic inequities. By combining targeted outreach to policymakers with community-driven insights, our research presents a replicable model for achieving impactful and sustainable policy change in support of vulnerable populations.
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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 | 0.031 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.026 | 0.021 |
| Scholarly communication | 0.015 | 0.005 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".