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Au-delà du diagnostic de trouble de stress post-traumatique : Reconnaître l’expérience de guerre des militaires français

2023· article· fr· W4387122677 on OpenAlexaffvenue
Servane Roupnel

Bibliographic record

VenueAnthropologica · 2023
Typearticle
Languagefr
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHumanitiesArtPolitical science

Abstract

fetched live from OpenAlex

Le traumatisme de guerre a fait l’objet de nombreuses études passant d’un régime de soupçon, envers des soldats accusés de simulation, à un régime de la reconnaissance par l’apparition d’un diagnostic médical officiel : le trouble de stress post-traumatique (TSPT). Pouvant toucher autant la population civile que la population militaire selon les critères diagnostic officiellement établis, il n’en reste pas moins que le milieu des armes présente de forts risques traumatiques du fait même de la profession militaire. Ainsi, poser la question du TSPT au sein de la sous-culture militaire, permet de concrétiser les enjeux contemporains que pose ce diagnostic. Tandis que cette mise en norme vient justifier le comportement, dit « anormal », de certains soldats, le diagnostic de TSPT reste sujet à réflexion notamment sur la façon dont il est vécu par les personnes atteintes. Car se faire diagnostiquer comme « post-traumatisé de guerre » ne va pas de soi. Le diagnostic implique de nombreux changements dans la vie du militaire que ce soit d’un point de vue personnel ou social. Cet article s’intéresse alors à l’expérience de militaires français post-traumatisés par un regard porté sur la perception du trouble pour l’individu atteint et ses proches à travers la prise en charge médicale du trouble de stress post-traumatique.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.309
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.031
GPT teacher head0.349
Teacher spread0.318 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2023
Admission routes2
Has abstractyes

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