Challenges of undocumented immigrants in Canada and the USA during the COVID-19 pandemic: a review
Bibliographic record
Abstract
Purpose Pandemics pose challenges to all groups of people and all aspects of human lives. Undocumented migrants are likely to face more challenges during global pandemics. The purpose of this paper is to explore the possible challenges of undocumented immigrants in Canada and the USA in the ongoing COVID-19 pandemic. Design/methodology/approach From existing literature, the authors examined the challenges of undocumented migrants in Canada and the USA and suggested recommendations to address those challenges at both policy and national levels. Findings The undocumented status of some international immigrants makes them vulnerable in their host nations. They face myriad challenges in their host countries, spanning from economic, health, social isolation and employment challenges, and these are further exacerbated during pandemics such as the ongoing COVID-19. The provision of culturally sensitive and safe policies may support this particular population, especially in times of crisis like the COVID-19 pandemic. Originality/value This paper provides critical insights into the possible intersections that worsen the vulnerability of undocumented migrants in pandemic crises like COVID-19. Further, this review serves to initiate the discourse on policy and interventions for undocumented immigrants during pandemics or disease outbreaks.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".