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Record W3048967011 · doi:10.18999/forids.50.7

Building Collective Resilience : The Role of Refugee Informal Support Networks

2020· article· ja· W3048967011 on OpenAlexaboutno aff
Jennifer Stewart

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2020
Typearticle
Languageja
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeResilience (materials science)Computer securityComputer sciencePolitical science

Abstract

fetched live from OpenAlex

With the arrival of 52,000 Syrian refugees to Canada in recent years and the challenges in adapting to their new life, a better understanding of informal support networks used by refugees will help enlighten governments and policy-makers regarding integration. This paper explores thedifferent informal interpersonal relationships experienced by Syrian refugees in British Columbiaand the roles each plays in building collective resilience. Fieldwork was conducted over threemonths in British Columbia and included semi-structured interviews with 26 former Syrian refugees and eight interviews with non-refugees. The research found six avenues of informal support thatprovide different functional benefits to former refugees and improve emotional well-being, culturaladjustment, and integration. The findings also show how experiences of trauma bond people into a shared group identity and how this further incites alt ruism and collective assistance, thusstrengthening the social group and building collective resilience. However, the findings also revealthat relying on any one informal support systems too much can be detrimental to psychologicalwell-being and slow integration. The implications of former refugees’ connections with informal support networks are discussed.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.890
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
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 head0.017
GPT teacher head0.296
Teacher spread0.279 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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