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Record W1670233201 · doi:10.3917/cnmi.131.0009

Échecs de mentalisation du trauma

2013· article· fr· W1670233201 on OpenAlexaff
Nicolas Berthelot, Karin Ensink, Lina Normandin

Bibliographic record

VenueCarnet de notes sur les maltraitances infantiles · 2013
Typearticle
Languagefr
FieldPsychology
TopicPsychoanalysis and Psychopathology Research
Canadian institutionsUniversité LavalUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Le présent article se veut la première partie d’un travail en deux volets s’intéressant à la mentalisation chez les victimes de maltraitance durant l’enfance. Le but de ce travail est d’outiller les intervenants cliniques à évaluer la façon dont réfléchissent les victimes de maltraitance à propos de leurs expériences traumatiques. Les cliniciens seront mieux outillés pour dépister les personnes les plus à risque de présenter des difficultés suite aux traumas et bénéficieront de pistes cliniques intéressantes permettant d’orienter les interventions thérapeutiques. Le présent volet s’intéresse spécifiquement aux échecs de mentalisation dans le discours, reflétant des facteurs de risque pour l’adaptation suite au trauma. Le second volet s’intéressera plus spécifiquement aux propos représentant une capacité de mentalisation préservée à l’égard des expériences traumatiques. La presque totalité du travail est dédiée à l’illustration clinique du phénomène, mais débute tout de même par un bref retour théorique sur le concept de la mentalisation et sur la relation entre les concepts de mentalisation et de trauma.

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)0.006
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 score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.007
Scholarly communication0.0040.004
Open science0.0010.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0090.001

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 head0.035
GPT teacher head0.322
Teacher spread0.287 · 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

Citations17
Published2013
Admission routes1
Has abstractyes

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