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Record W4391648128 · doi:10.2196/56242

Homestay Hosting Dynamics and Refugee Well-Being: Protocol for a Scoping Review

2024· review· en· W4391648128 on OpenAlexafffundvenue
Areej Al‐Hamad, Yasin M. Yasin, Kateryna Metersky, Sepali Guruge, Khadija Mahsud

Bibliographic record

VenueJMIR Research Protocols · 2024
Typereview
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsToronto Metropolitan University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsRefugeeProtocol (science)Computer scienceDynamics (music)PsychologyMedicinePolitical scienceAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The process of refugee resettlement and integration into new communities is a complex and multifaceted challenge, not only for the refugees themselves but also for the host families involved in homestay housing arrangements. While these homestay arrangements are designed to facilitate smoother transitions and enhance the well-being of refugees, the nuanced dynamics of these interactions and their overall impact on both refugees and their host families remain underexplored. Understanding the experiences of refugees and their host families is vital for effective refugee settlement, integration, and well-being. However, the intricacies of homestay refugee hosting, their interactions with host families, and the impact on their well-being are still unclear and ambiguous. OBJECTIVE: The aim of this scoping review is to examine the breadth of literature on the experiences of refugees living in homestay arrangements with their host families. This review seeks to understand how these dynamics influence refugee well-being, including their integration, social connections, and mental health. Additionally, this scoping review aims to synthesize existing literature on homestay hosting dynamics, focusing on the experiences of refugees and their host families, to identify gaps in knowledge and suggest areas for future research. METHODS: This scoping review follows Joanna Briggs Institute methodology and will search databases such as CINAHL, SOCIndex, MEDLINE through EBSCO; APA PsycInfo, Scopus through OVID; and Web of Science Core Collection, ProQuest Dissertations, and Theses, and SciELO Citation Index, focusing on literature from 2011 onward, in English, in relation to refugee groups in different host countries, including all types of literature. Literature will be screened by 2 independent reviewers, with disagreements resolved by consensus or a third reviewer. A custom data extraction tool will be created by the research team. RESULTS: The results will be organized in tables or diagrams, accompanied by a narrative overview, emphasizing the main synthesized findings related to the dynamics of homestay hosting with host families and refugee well-being. No critical appraisal will be conducted. This scoping review is expected to identify research gaps that will inform the development of homestay refugee hosting models, policies, and practices. It will also offer insights into best practices and policy recommendations to improve homestay hosting programs, ultimately contributing to more effective refugee settlement and integration strategies. CONCLUSIONS: Understanding the intricate dynamics of homestay hosting arrangements is crucial for developing policies and programs that support the well-being of refugees and the families that host them. This scoping review will shed light on the current knowledge landscape, identify research gaps, and suggest ways to enhance the homestay hosting experience for all parties involved. Through this work, we aim to contribute to the development of more inclusive, supportive, and effective approaches to refugee hosting, resettlement, and integration. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/56242.

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)0.069
metaresearch head score (Gemma)0.084
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.084
Threshold uncertainty score0.367

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0690.084
Meta-epidemiology (narrow)0.0050.005
Meta-epidemiology (broad)0.0140.014
Bibliometrics0.0200.017
Science and technology studies0.0050.005
Scholarly communication0.0080.010
Open science0.0050.007
Research integrity0.0080.007
Insufficient payload (model declined to judge)0.0840.013

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 head0.428
GPT teacher head0.684
Teacher spread0.255 · 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 designSystematic review
Domainnot available
GenreProtocol

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

Citations4
Published2024
Admission routes3
Has abstractyes

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