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Record W2344002883 · doi:10.1080/20581831.2016.1153358

The collapse of social networks among Syrian refugees in urban Jordan

2016· article· en· W2344002883 on OpenAlexafffund
Matthew Russell Stevens

Bibliographic record

VenueContemporary Levant · 2016
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsYork University
FundersYork University
KeywordsRefugeeSyrian refugeesMiddle EastVariety (cybernetics)Social network (sociolinguistics)Social supportPalestinian refugeesPolitical scienceDevelopment economicsEconomic growthGeographySocial psychologyPsychologyComputer scienceEconomicsSocial media

Abstract

fetched live from OpenAlex

Strong social networks have been shown to correlate with improved economic outcomes and emotional wellbeing in urban refugee populations. In the Middle East and North Africa, social networks are based on a wide variety of relational identities that interconnect, suggesting an array of opportunities for community self-support. However, this research shows that Syrian refugees living in Irbid, Jordan, no longer actively turn to social networks for support. The financial and emotional strain of exile and the failure of international aid agencies to maintain pre-existing social connections and to support the development of new ones have led to the collapse of social networks among Syrian refugees in Jordan.

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)0.000
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 score0.149
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.023
GPT teacher head0.302
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.

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

Citations60
Published2016
Admission routes2
Has abstractyes

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