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Record W2524530786

Salvadoran refugees: a case study of stress and coping

2015· article· en· W2524530786 on OpenAlexaboutno aff

Bibliographic record

VenueK-State Research Exchange (Kansas State University) · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeCoping (psychology)PsychologyPolitical scienceSocial psychologyClinical psychologyLaw
DOInot available

Abstract

fetched live from OpenAlex

David (1970) describes migration as "an interruption and frustration of natural life expectations, with all the related anxieties and potential damage to the self concept" (p.79).Migration, he says, induces cognitive stress, forcing the immigrant to change familiar images and build a new cognitive map.Dodge (1973) and Roskies (1978) point to the stress of migration, but also to the lack of agreement regarding the most stressful stages of adaptation.In their study of Vietnamese in the United States, Lin et al.(1982) observed that three years after arrival the majority of refugees were more or less settled.However, looking at previous clinical and field experience, they found that depression and anxiety could worsen with time as a result of the "losses" experienced, as well as "culture shock", which contributed to a gradual increase in cases needing attention by mental health workers.In their opinion, the increase in depression and anxiety was caused by accumulation of stress due to new behavior yet to be learned and new situations to be coped with.Among North African immigrants to Canada, Lasry (1977) found that initially high stress scores became lower after up to eight years of residence.However, with Portuguese immigrants to Canada, Roskies (1978) did not observe a significant relation between symptom scores and duration of residence.Most of the adjustment appeared to take place soon after arrival.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
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 head0.157
GPT teacher head0.333
Teacher spread0.176 · 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 designQualitative
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
Published2015
Admission routes1
Has abstractyes

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