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Record W2293935617 · doi:10.3917/cpsy.068.0067

Entre honte et culpabilité, stigmates de la femme enceinte après une Interruption Médicale de Grossesse

2016· article· fr· W2293935617 on OpenAlexaff
Jessica Shulz, Bérengère Beauquier‐Maccotta, Marie-José Soubieux, Marie-Emmanuelle Mériot, Diane de Wailly, Sylvain Missonnier

Bibliographic record

VenueChamp psy · 2016
Typearticle
Languagefr
FieldPsychology
TopicPsychoanalysis and Psychopathology Research
Canadian institutionsSte. Anne's Hospital
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

À partir d’un matériel issu d’une recherche clinique se référant à la psychanalyse en milieu hospitalier, les auteurs se proposent d’explorer les traces laissées par la perte d’un enfant à la suite d’une Interruption Médicale de Grossesse, lors de la grossesse suivante. L’étude de la honte et de la culpabilité dans ce contexte permet de donner des repères sémiologiques et psychopathologiques pertinents dans le cadre d’une prévention primaire et secondaire des troubles de la parentalité et des dysharmonies relationnelles précoces.

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)0.009
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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.004
Scholarly communication0.0010.001
Open science0.0000.002
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 head0.065
GPT teacher head0.418
Teacher spread0.353 · 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

Citations10
Published2016
Admission routes1
Has abstractyes

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