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Record W2953763340 · doi:10.3917/bupsy.561.0163

Les représentations d’attachement, les relations d’objet et le jeu des enfants victimes de mauvais traitements

2019· article· fr· W2953763340 on OpenAlexaff
Mélissa Paquette, Miguel M. Terradas, Saralea E. Chazan, Cécilanne Lepage-Voyer, Rosalie Guillemette

Bibliographic record

VenueBulletin de psychologie · 2019
Typearticle
Languagefr
FieldPsychology
TopicPsychoanalysis and Psychopathology Research
Canadian institutionsSanté MontérégieCorporation d’Aménagement et de Protection de la Sainte-AnneUniversité de SherbrookeCentre Integre de Sante et de Services Sociaux de Laval
Fundersnot available
KeywordsHumanitiesSociologyArtPsychology

Abstract

fetched live from OpenAlex

Les auteurs de cette étude visent à décrire les représentations d’attachement, les relations d’objet, ainsi que le jeu de quinze enfants d’âge scolaire, ayant vécu des traumas relationnels précoces, à l’aide de deux situations de jeu, l’une structurée et l’autre libre. Deux instruments, les histoires d’attachement à compléter et le Children’s Play Therapy Instrument , ont permis d’analyser les représentations de l’enfant. Les résultats obtenus suggèrent que ces enfants ont des représentations soutenantes et non-rejetantes de leurs figures parentales, alors que leurs représentations des relations d’objet tendent à être plus immatures que matures. Toutefois, cette différence n’atteint pas le seuil de significativité statistique.

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)0.001
metaresearch head score (Gemma)0.007
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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.083
GPT teacher head0.470
Teacher spread0.388 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

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