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Record W2316797127 · doi:10.1177/2156869314555582

The Impact of Armed Conflict in the Country of Origin on Mental Health after Migration to Canada

2014· article· en· W2316797127 on OpenAlexaffabout
Marie-Pier Joly, Blair Wheaton

Bibliographic record

VenueSociety and Mental Health · 2014
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsArmed conflictMental healthAnxietyDepression (economics)PsychologyPsychiatryMedicinePolitical science

Abstract

fetched live from OpenAlex

This article examines mental health differences among migrants who emigrated from both armed conflict countries and non–conflict countries versus native-born Canadians. We propose that the impact of armed conflict on mental health depends on defining characteristics of the conflict. Our analysis of migrants to Toronto, Canada, suggests that exposure to major intrastate conflicts have long-term impacts on depression among women and anxiety levels among men after migration. We assess the role of different stages and types of stress proliferation in explaining these differences. Postmigratory chronic stress helps explain differences in depression between migrant women who experienced conflict and both those who did not and Canadian-born women. Conversely, traumatic stress that occurred during the ongoing armed conflict at time of migration helped explain differences in anxiety between migrant men exposed to conflict and both migrant men not exposed and Canadian-born men.

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 score0.708
Threshold uncertainty score0.281

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 head0.016
GPT teacher head0.360
Teacher spread0.345 · 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

Citations11
Published2014
Admission routes2
Has abstractyes

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