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Record W4411170080 · doi:10.17161/gjcpp.v8i2.20723

From Passive Recipient to Community Advocate: Reflections on Peer-Based Resettlement Programs for Arabic-Speaking Refugees in Canada

2017· article· en· W4411170080 on OpenAlexaffabout
Joel John Badali, Santiago Grande, Keghani Mardikian

Bibliographic record

VenueGlobal Journal of Community Psychology Practice · 2017
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsRegional Municipality of WaterlooMcGill University
FundersKultúrna a Edukacná Grantová Agentúra MŠVVaŠ SR
KeywordsArabicRefugeeSociologyGender studiesMedia studiesPolitical scienceLawLinguistics

Abstract

fetched live from OpenAlex

The current study explores the impacts of peer support programs on recently resettled refugees to Canada. This research uses qualitative data that was collected from service users as part of a broader formative evaluation of a regional mental health initiative; the Promise of Partnership. This initiative arose from a need to proactively address the resettlement issues experienced by refugees in the Region of Waterloo. The analysis focusses specifically on the impacts to refugees involved in Arabic-speaking peer support groups as understood through the theoretical framework of the ecological model. Findings from the analysis locate key benefits to participants across the interpersonal, organizational, and community levels of the model, revealing the interwoven and impactful nature of peer support amongst participants and their broader community. Given the unprecedented influx of Syrian refugees to Canada, we argue for the continued implementation of peer support groups as a source of mental wellness promotion, empowerment, and a broadened sense of community.

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)0.005
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.451
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.003
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 head0.141
GPT teacher head0.497
Teacher spread0.357 · 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.

Study designNot applicable
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

Citations9
Published2017
Admission routes2
Has abstractyes

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