Structural Origins of Poor Health Outcomes in Documented Temporary Foreign Workers and Refugees in High-Income Countries: A Review
Bibliographic record
Abstract
Despite growing evidence of racial and institutional discrimination on minoritized communities and its negative effect on health, there are still gaps in the current literature identifying health disparities among minoritized communities. This review aims to identify health barriers faced by relatively less studied migrant subgroups including documented temporary foreign workers and refugees residing in high-income Organisation for Economic Co-operation and Development (OECD) countries focusing on the structural origins of differential health outcomes. We searched Medline, CINAHL, and Embase databases for papers describing health barriers for these groups published in English between 1 January 2011 and 30 July 2021. Two independent reviewers conducted a title, abstract, and full text screening with any discrepancies resolved by consensus or a third reviewer. Extracted data were analyzed using an inductive thematic analysis. Of the 381 articles that underwent full-text review, 27 articles were included in this review. We identified housing conditions, immigration policies, structural discrimination, and exploitative labour practices as the four major emerging themes that impacted the health and the access to healthcare services of our study populations. Our findings highlight the multidimensional nature of health inequities among migrant populations and a need to examine how the broader context of these factors influence their daily experiences.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".