MétaCan
Menu
Back to cohort
Record W4214843422 · doi:10.3390/ijerph19052981

(Not That) Essential: A Scoping Review of Migrant Workers’ Access to Health Services and Social Protection during the COVID-19 Pandemic in Australia, Canada, and New Zealand

2022· review· en· W4214843422 on OpenAlexaboutno aff
Satrio Nindyo Istiko, Jo Durham, Lana Elliott

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2022
Typereview
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicPrecarityRacismImmigrationPolitical scienceEconomic growthSocial protectionMigrant workersCoronavirus disease 2019 (COVID-19)MedicineEconomics

Abstract

fetched live from OpenAlex

Migrant workers have been disproportionately affected by the COVID-19 pandemic. To examine their access to health services and social protection during the pandemic, we conducted an exploratory scoping review on experiences of migrant workers in three countries with comparable immigration, health, and welfare policies: Australia, Canada, and New Zealand. After screening 961 peer-reviewed and grey literature sources, five studies were included. Using immigration status as a lens, we found that despite more inclusive policies in response to the pandemic, temporary migrant workers, especially migrant farm workers and international students, remained excluded from health services and social protection. Findings demonstrate that exploitative employment practices, precarity, and racism contribute to the continued exclusion of temporary migrant workers. The interplay between these factors, with structural racism at its core, reflect the colonial histories of these countries and their largely neoliberal approaches to immigration. To address this inequity, proactive action that recognizes and targets these structural determinants at play is essential.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.845
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.418
GPT teacher head0.555
Teacher spread0.137 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations37
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Environmental Research and Public HealthSame topicEmployment and Welfare StudiesFrench-language works237,207