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Record W2784022515 · doi:10.1192/s1749367600004628

The mental health needs of immigrant workers in Gulf countries

2014· editorial· en· W2784022515 on OpenAlexaff
Muhammad Ajmal Zahid, Mohammad Alsuwaidan

Bibliographic record

VenueInternational Psychiatry · 2014
Typeeditorial
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRepatriationMental healthEthnic groupImmigrationMental illnessRehabilitationPsychiatryInterpreterService (business)MedicineRefugeePolitical scienceEconomic growthBusinessLaw

Abstract

fetched live from OpenAlex

The oil-rich member states of the Gulf Cooperation Council (GCC) attract large numbers of migrant workers. The reported rates of psychiatric morbidity among these migrant workers are higher than among nationals, while the mental health services in the GCC countries remain inadequate in terms of both staff and service delivery. The multi-ethnic origin of migrants poses considerable challenges in this respect. The development of mental illness in migrants, especially when many of them remain untreated or inadequately treated, results in their premature repatriation, and the mentally ill migrant ends up facing the same economic hardships which led to migration in the first place. The availability of trained interpreters and transcultural psychiatrists, psychologists and social workers should make psychiatric diagnoses more accurate. Suitable rehabilitation services are also needed.

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)0.001
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.036
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.007
GPT teacher head0.325
Teacher spread0.319 · 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
GenreEditorial

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

Citations11
Published2014
Admission routes1
Has abstractyes

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