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Record W7128635804 · doi:10.7202/1122695ar

La croissance post-traumatique chez les jeunes à la suite d’une catastrophe naturelle : une recension narrative des écrits

2025· article· fr· W7128635804 on OpenAlexaffvenue
Ann-Sophie Simard, Eve Pouliot, Christine Gervais

Bibliographic record

VenueRevue québécoise de psychologie · 2025
Typearticle
Languagefr
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversité du Québec en OutaouaisUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsNarrativeAmbivalenceContext (archaeology)Subjectivity

Abstract

fetched live from OpenAlex

L’objectif de cet article est de faire état des connaissances actuelles sur la croissance post-traumatique des jeunes exposés à une catastrophe naturelle. Pour ce faire, une revue narrative systématisée des articles sur le sujet a été menée entre le printemps et l’été 2024. Ainsi, cet article permet de mieux comprendre que la croissance post-traumatique est un phénomène possible chez les jeunes et que de nombreux facteurs, tant individuels qu’environnementaux, peuvent influencer ce processus de changement. De plus, il expose en quoi une meilleure compréhension de ce phénomène permettra d’intervenir plus adéquatement auprès des jeunes en contexte post-catastrophe.

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)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.007
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.052
GPT teacher head0.394
Teacher spread0.341 · 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 designSystematic review
Domainnot available
GenreReview

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
Published2025
Admission routes2
Has abstractyes

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