MétaCan
Menu
Back to cohort
Record W3158656474 · doi:10.15273/allons-y.v2i0.10055

Syrian Refugee Children And Mental Health Trauma

2020· article· en· W3158656474 on OpenAlexvenueno aff
Kathleen O’Brien

Bibliographic record

VenueAllons-y Journal of Children Peace and Security · 2020
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeMental healthInternally displaced personHumanitarian crisisSpanish Civil WarPolitical scienceDisplaced personPopulationMedicineEconomic growthStigma (botany)Environmental healthPsychiatryLaw

Abstract

fetched live from OpenAlex

In 2015, the United Nations International Children’s Emergency Fund (UNICEF) named Syria as the most dangerous place on earth to be a child (UNICEF, 2). Since the onset of civil war in 2011, nearly 4.8 million Syrians are refugees outside of Syria and approximately 6 million are internally displaced (United Nations Office for the Coordination of Humanitarian Affairs, 2016). While some refugees have successfully resettled in North American and European nations, many remain in limbo in refugee camps. What is most staggering about the population of affected persons is that nearly half, approximately 6 million, are children (UNICEF, 2016). Nearly all of these children have been subjected to trauma that has manifested in a variety of ways. They have often been subjected to or witnessed violence and have experienced the loss of one or more of their caregivers. Refugees face difficulty accessing psychological and health services and are met with the stigma surrounding mental health in countries including Lebanon and Turkey, regions that many refugee children have fled to. In the absence of these supports, the mental trauma a child is experience can impact learning and development and have disastrous impacts on their future.

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 score0.410
Threshold uncertainty score0.766

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 integrity0.0000.001
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 head0.012
GPT teacher head0.292
Teacher spread0.281 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueAllons-y Journal of Children Peace and SecuritySame topicMigration, Health and TraumaFrench-language works237,207