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Record W3176918495 · doi:10.15273/allons-y.v3i0.10058

Refugee Youth and Mental Health: Principles for Resettlement Support

2020· article· en· W3176918495 on OpenAlexvenueno aff
Emily Pelley

Bibliographic record

VenueAllons-y Journal of Children Peace and Security · 2020
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeMental healthPsychological resiliencePerspective (graphical)Political scienceDisplacement (psychology)PsychologyDisplaced personCriminologyPublic relationsEconomic growthSociologySocial psychologyPsychiatryPsychotherapistLaw

Abstract

fetched live from OpenAlex

The issue of young people on the move has attracted significant international attention as the amount of displacement due to armed conflict has steadily increased in recent years. The UNHCR reports that 68.5 million people have been displaced worldwide, with just over half of them being under the age of 18.1 Armed conflict often forces families to flee their homes and communities in search of safety. For those who can go to a new country there are both benefits and challenges to navigate. The experiences of youth displacement because of armed conflict is an area that needs further research.This paper explores the current situation of youth displacement and the importance of informed mental health support throughout their transition experience in a new country. A young person’s resilience through the experience of integrating into a new home is not merely a description of their personality but a combination of the personal and social resources that can positively impact their well-being. This social ecological perspective of resilience is a useful framework for responding to the needs of young refugees.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.429
Threshold uncertainty score0.483

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 head0.039
GPT teacher head0.333
Teacher spread0.294 · 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 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

Citations1
Published2020
Admission routes1
Has abstractyes

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