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Record W6992563777

Les corrélats psychosociaux de la violence des hommes envers leur conjointe

2020· other· fr· W6992563777 on OpenAlexaboutno aff

Bibliographic record

VenueCorpus Université Laval (Université Laval) · 2020
Typeother
Languagefr
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationSocializationPoison controlDomestic violence
DOInot available

Abstract

fetched live from OpenAlex

L'étude cherche à préciser les corrélats psychosociaux de la violence des hommes envers leur conjointe. La population se compose de 60 couples de langue française du Québec répartis dans le groupe clinique où l'homme est diagnostiqué avoir des comportements violents envers sa conjointe et le groupe contrôle où l'homme ne fait pas l'objet de ce diagnostic. Les agresseurs affichent une attitude très peu stéréotypées envers les rôles des hommes et des femmes, ils s'attribuent beaucoup moins de comportements violents qu'en rapporte sa conjointe et ils affichent plus qu'elle des problèmes psychopathologiques. Ils adoptent un style d'attachement sécurisant et sa conjointe possède généralement un style d'attachement différent du sien. Les couples aux prises avec un problème de violence souffrent de détresse conjugale. La dépression majeure, les antécédents judiciaires et la dépendance à l'alcool sont de bons prédicteurs de violence chez les hommes alors que l'ajustement dyadique et les antécédents judiciaires du conjoint sont de bons prédicteurs.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.260
Threshold uncertainty score0.518

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.014
GPT teacher head0.234
Teacher spread0.220 · 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 designObservational
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

Citations0
Published2020
Admission routes1
Has abstractyes

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