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Record W4385200240 · doi:10.31688/abmu.2023.58.2.13

COVID-19 AND ITS IMPLICATIONS FOR THE EXPATRIATE COMMUNITIES IN SAUDI ARABIA

2023· article· en· W4385200240 on OpenAlexaff
Saad Arslan Iqbal, Arun Vijay Subbarayalu, Namra Tayyab

Bibliographic record

VenueArchives of the Balkan Medical Union · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)ExpatriatePolitical scienceHumanitiesMedicineArtVirologyOutbreak

Abstract

fetched live from OpenAlex

COVID-19 et ses implications pour les communautés expatriées en Arabie SaouditeLa pandémie de maladie à coronavirus 2019 (COVID-19) est une préoccupation majeure dans le monde, en particulier pour les travailleurs migrants qui sont confrontés à des difficultés sans précédent dans toutes les régions.Cependant, il existe peu de recherches sur la façon dont ce groupe démographique vulnérable a fait face aux défis de la pandémie de COVID-19.Par conséquent, cet examen narratif a été réalisé pour mettre en évidence les problèmes auxquels les expatriés sont confrontés pendant la pandémie de COVID-19, avec un accent particulier sur les personnes vivant en Arabie saoudite.Certaines des pratiques de lutte contre la pandémie de COVID-19 comprennent la fourniture de communications sanitaires en temps opportun, la fourniture de services de santé équitables à tous les travailleurs étrangers, le suivi électronique de l'état de santé des citoyens et des résidents, l'amélioration des conditions de vie des travailleurs migrants et le maintien d'un approvisionnement ininterrompu.alimentaire, la mise en œuvre ABSTRACTThe coronavirus disease 2019 (COVID-19) pandemic is a major concern worldwide, especially for migrant workers who are facing unprecedented hardships in all regions.However, there is limited research on how this vulnerable demographic group has coped with the challenges of the COVID-19 pandemic.Therefore, this narrative review was conducted to highlight the issues expatriates are facing during the COVID-19 pandemic, with a particular focus on the people living in Saudi Arabia.Some of the practices to combat the COVID-19 pandemic include providing timely health communications, providing equitable health services to all foreign workers, electronically tracking the health status of citizens and residents, and improving the living conditions of migrant workers, and maintaining an uninterrupted supply of food, implementation of economic reforms in the labor sector, effective border closures and travel restrictions, and regulation of social and religious gatherings.This study also proposes some recommendations to ensure the safety, health and well-being of expatriate communities around the world in pandemic situations.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score0.402

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.002
Scholarly communication0.0040.002
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0120.001

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.

Opus teacher head0.081
GPT teacher head0.313
Teacher spread0.232 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations1
Published2023
Admission routes1
Has abstractyes

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