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Record W4322583243 · doi:10.7565/ssp.v5.6692

Social Networks and Support to Older People in Refugee Situation in Western Countries

2022· article· en· W4322583243 on OpenAlexaffabout
Prince Chiagozie Ekoh, Christine A. Walsh, Elizabeth Onyedikachi George, Anthony Obinna Iwuagwu

Bibliographic record

VenueSocial Science Protocols · 2022
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsRefugeeScopusSocial exclusionInclusion (mineral)Social supportForced migrationSocial network (sociolinguistics)Political sciencePublic relationsPsychologySociologySocial psychologyMEDLINESocial media

Abstract

fetched live from OpenAlex

Background: Forced migration of humans as a result of conflict continues to be a global problem. Many of the refugees displaced and made vulnerable by conflict induced forced migration are older adults. These older adults may lose their social networks and support as a result of the conflicts leading to migration and be unable to recreate them, making them more vulnerable. This review aims to describe the social network and support situation of older adults in refugee situation as presented in global literature. Methods/Design: The five steps of Arksey and O’Malley’s (2005) framework to search multiple databases from inception till June 2021 will be followed. MeSH terms and keywords, e.g., “older refugees”, “refugees”, and “social network”, “social support”, will be adopted for the following databases: SocINDEX, PsychINFO, Social Work Abstracts, Sociology Abstracts, Social Services Abstracts, Web of Science and/or Scopus, Canadian electronic library. Citations will be screened (title/abstract and full text) using predefined inclusion and exclusion criteria. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) will be used to describe the process of data inclusion and exclusion. Discussion: This review will reveal gaps in the provision of social support to older refugees and inform policy development for the improvement of support to older refugees.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.339
Threshold uncertainty score0.602

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.031
GPT teacher head0.414
Teacher spread0.384 · 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 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

Citations5
Published2022
Admission routes2
Has abstractyes

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