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Record W2992414129 · doi:10.7202/1065864ar

Processus de changement des adolescents auteurs de violences sexuelles

2019· article· fr· W2992414129 on OpenAlexvenueno aff
Pascal Roman, Thérèse Cuttelod, Sylvie Espeil-Marc, Dorothée Gorry, Frédérique Lavèze, Magali Ravit

Bibliographic record

VenueCriminologie · 2019
Typearticle
Languagefr
FieldPsychology
TopicPsychoanalysis and Psychopathology Research
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPsychologyPhilosophy

Abstract

fetched live from OpenAlex

Cet article présente les principales avancées issues d’une recherche menée conjointement sur deux sites cliniques, en Suisse et en France, et consacrée à l’évaluation des processus de changement des adolescents auteurs de violences sexuelles. L’objectif est de dégager les principaux indicateurs cliniques de ces changements, à partir d’une étude longitudinale portant sur un petit nombre d’adolescents (N =9), engagés dans une démarche psychothérapeutique sous mandat judiciaire en groupe. L’étude s’appuie sur une démarche qualitative, qui associe principalement deux types de recueil de données cliniques : épreuves projectives en test-retest d’une part et enregistrement des verbatims de séances de groupe d’autre part. À partir de l’analyse croisée de ces données, un certain nombre d’indicateurs cliniques peuvent être mis en évidence, qui permettent d’esquisser une modélisation des processus de changement chez les adolescents. Au-delà, les éléments de compréhension qui émergent de la recherche permettent de tracer des perspectives pour le soin psychothérapeutique des adolescents.

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)0.010
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.297
GPT teacher head0.455
Teacher spread0.158 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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