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Record W2341293943 · doi:10.5296/ijsw.v3i1.8814

Documenting Refugee Stories: Resettlement and Integration Challenges of East African Refugees

2016· article· en· W2341293943 on OpenAlexaffabout
Nimo Bokore

Bibliographic record

VenueInternational Journal of Social Work · 2016
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsYork University
Fundersnot available
KeywordsRefugeeForced migrationImmigrationGeopoliticsDisplaced personPolitical scienceGender studiesMiddle EastEconomic growthSociologyLawPolitics

Abstract

fetched live from OpenAlex

<p>Recently we have witnessed forced displacement and migration on a globalized scale and the human suffering that this creates. Since early 2014, events have escalated in Syria and other Middle Eastern countries as religious-based interest groups such as ISIS push to make territorial gains. One cannot escape media reports documenting the devastating impact this has as refugees try to reach safety, whether by crossing the Mediterranean Sea or European borders.</p><p>In this article, I present my personal experience of refugee life as a survivor of war and multiple forced migrations and as a professional service provider to immigrants and refugees who make Canada their new home. In many ways, my story is the story of other refugees who also encounter issues of race, religion and geopolitical locations as they migrate and resettle in a new country.</p>

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.514
Threshold uncertainty score0.498

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 head0.032
GPT teacher head0.367
Teacher spread0.335 · 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

Citations2
Published2016
Admission routes2
Has abstractyes

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