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Record W1990680548 · doi:10.1080/13648470410001678631

Sociosomatic theory in Vietnamese immigrants' narratives of distress

2004· article· en· W1990680548 on OpenAlexaffabout
Danielle Groleau, Laurence J. Kirmayer

Bibliographic record

VenueAnthropology and Medicine · 2004
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsMcGill University
Fundersnot available
KeywordsVietnameseNarrativeDistressIndignationPsychologyExplanatory modelFeelingAngerSocial psychologyInjusticeSociologyImmigrationHistoryClinical psychologyPolitical sciencePoliticsEpistemology

Abstract

fetched live from OpenAlex

We examined the symptom experience and illness explanations of Vietnamese immigrants to Canada through narratives collected during a study of pathways and barriers to mental health care. The narratives presented two culture-related explanatory models: phong thâp and uâ't u'ć. Common elements in the narratives of those who suffered from uâ't u'ć were experiences of injustice and indignation, along with the persistent inability to denounce these injustices because of the sufferer's social status. In contrast, phong thâp - an explanation analogous to rheumatism - was a socially acceptable way to describe distress that was attributed to depletion of energy, cold and environmental effects. Talk about phong thâp also served as an idiom of distress that permitted older people to express negative feelings about their life situation in Canada in a socially acceptable way. The contrast between these models throws into relief the complex interaction of explanatory models and idioms of distress in the co-construction of narratives of distress.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.112
Threshold uncertainty score0.223

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0100.026
Scholarly communication0.0070.005
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.373
Teacher spread0.357 · 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 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

Citations84
Published2004
Admission routes2
Has abstractyes

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