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Record W2162284297 · doi:10.1177/1363461513506529

Local responses to trauma: Symptom, affect, and healing

2013· editorial· en· W2162284297 on OpenAlexaff
Devon E. Hinton, Laurence J. Kirmayer

Bibliographic record

VenueTranscultural Psychiatry · 2013
Typeeditorial
Languageen
FieldSocial Sciences
TopicCultural, Psychoanalytic, and Sociopolitical Reflections
Canadian institutionsMcGill University
Fundersnot available
KeywordsDistressPsychological interventionAffect (linguistics)PsychotherapistCognitionMoodPsychologyClinical psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

This article provides an introduction to the thematic issue of Transcultural Psychiatry on local responses to trauma. To illustrate how local responses to trauma may be therapeutic, we consider the multiple dimensions or domains that may be targeted by healing rituals and interventions. We then outline a theoretical model of the generation of trauma-related symptoms and distress. We present the multiplex model of symptom generation which posits multiple cognitive, social, and physiological mechanisms by which various triggers can lead to severe distress among trauma victims in acute episodes, and which may be targeted in treatment. More persistent forms of distress can be explained in terms of the effects of persistent mood states and associated modes of cognitive processing and behavior that render individuals vulnerable to chronic symptoms and acute exacerbations. The beneficial effects of healing rituals and interventions may occur, in part, by inducing positive affective states associated with a flexible mind-set. We conclude by summarizing some of the contributions of the papers in this issue to understanding local therapeutic processes of healing.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.077
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.024
GPT teacher head0.372
Teacher spread0.349 · 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.

Study designNot applicable
Domainnot available
GenreEditorial

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

Citations63
Published2013
Admission routes1
Has abstractyes

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