MétaCan
Menu
Back to cohort
Record W3080573769 · doi:10.1017/9781108602105.003

The Role of Family Functioning in Refugee Child and Adult Mental Health

2020· book-chapter· en· W3080573769 on OpenAlexaff
Matthew Hodes, Nasima Hussain

Bibliographic record

VenueCambridge University Press eBooks · 2020
Typebook-chapter
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsMcGill University
Fundersnot available
KeywordsRefugeeFamily resilienceMental healthStressorPsychologyPsychological resilienceFamily disruptionFamily conflictFamily lifeDevelopmental psychologyPsychiatrySocial psychologyPolitical scienceSociologySocioeconomics

Abstract

fetched live from OpenAlex

Refugees experience adversities and changes in their lives that profoundly impact family life. Family values and relationships may influence how those events are experienced and the ability of family members to cope with them. The frequent consequences of violence exposure and war events, displacement and resettlement include significant losses and disruptions to relationships and family and community life. Such experiences are associated with a higher prevalence of psychiatric disorders, especially PTSD and depression. The stressors may strain family relations and result in insecure infant-parent attachment and family conflict. The process of migration and resettlement may also provide opportunities for assimilation into a safer and more affluent society and enable changes in family relationships, with opportunities for new, rewarding roles for some family members but for others occupational and status decline and low morale. Over time, refugees’ mental health and social adaptation improves. Refugees show significant resilience - most cope well even when faced with harrowing adversities - but this is more likely in the presence of confiding and supportive family relationships.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.009
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.016
GPT teacher head0.233
Teacher spread0.217 · 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 source (direct Gemma or distilled Codex), 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

Citations13
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueCambridge University Press eBooksSame topicMigration, Health and TraumaFrench-language works237,207