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Record W2808921551 · doi:10.1186/s12889-018-5689-x

Bibliometric analysis of global migration health research in peer-reviewed literature (2000–2016)

2018· article· en· W2808921551 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBMC Public Health · 2018
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsScopusMedicinePublic healthRefugeeBiostatisticsPeer reviewMental healthPsychosocialGlobal healthHealth policyEnvironmental healthMEDLINEFamily medicinePolitical sciencePsychiatryNursingLaw

Abstract

fetched live from OpenAlex

BACKGROUND: The health of migrants has become an important issue in global health and foreign policy. Assessing the current status of research activity and identifying gaps in global migration health (GMH) is an important step in mapping the evidence-base and on advocating health needs of migrants and mobile populations. The aim of this study was to analyze globally published peer-reviewed literature in GMH. METHODS: A bibliometric analysis methodology was used. The Scopus database was used to retrieve documents in peer-reviewed journals in GMH for the study period from 2000 to 2016. A group of experts in GMH developed the needed keywords and validated the final search strategy. RESULTS: The number of retrieved documents was 21,457. Approximately one third (6878; 32.1%) of the retrieved documents were published in the last three years of the study period. In total, 5451 (25.4%) documents were about refugees and asylum seekers, while 1328 (6.2%) were about migrant workers, 440 (2.1%) were about international students, 679 (3.2%) were about victims of human trafficking/smuggling, 26 (0.1%) were about patients' mobility across international borders, and the remaining documents were about unspecified categories of migrants. The majority of the retrieved documents (10,086; 47.0%) were in psychosocial and mental health domain, while 2945 (13.7%) documents were in infectious diseases, 6819 (31.8%) documents were in health policy and systems, 2759 (12.8%) documents were in maternal and reproductive health, and 1918 (8.9%) were in non-communicable diseases. The contribution of authors and institutions in Asian countries, Latin America, Africa, Middle East, and Eastern European countries was low. Literature in GMH represents the perspectives of high-income migrant destination countries. CONCLUSION: Our heat map of research output shows that despite the ever-growing prominence of human mobility across the globe, and Sustainable Development Goals of leaving no one behind, research output on migrants' health is not consistent with the global migration pattern. A stronger evidence base is needed to enable authorities to make evidence-informed decisions on migration health policy and practice. Research collaboration and networks should be encouraged to prioritize research in GMH.

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.

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)0.021
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesBibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0210.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0700.417
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.200
GPT teacher head0.500
Teacher spread0.300 · 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