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Record W3025397354 · doi:10.7202/1068924ar

Portrait des violences subies par des femmes en contexte conjugal

2020· article· fr· W3025397354 on OpenAlexaffvenue
Guisela Patard, Frédéric Ouellet, Chloé Leclerc, Marie‐Marthe Cousineau

Bibliographic record

VenueService social · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesVictimisationPolitical scienceArtPoison controlSuicide preventionMedicine

Abstract

fetched live from OpenAlex

Les violences au sein du couple peuvent s’exercer de différentes manières (physique, sexuelle, psychologique, économique), varier en fréquence, en intensité et évoluer dans le temps. À partir de la méthodologie des calendriers d’histoire de vie et d’un questionnaire, la présente étude explore les expériences de victimisation de 75 femmes ayant vécu au moins une forme de violence au sein du couple dans les trois années précédant l’entrevue. L’objectif est la compréhension des violences et de leurs paramètres. Les résultats montrent une hétérogénéité importante entre les types de violence tant du point de vue des paramètres que de l’évolution et soulignent l’intérêt d’étudier les types de violence de manière individuelle, mais également leurs cooccurrences.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.420
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.004
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.076
GPT teacher head0.334
Teacher spread0.258 · 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; both teacher heads agree on what is shown here.

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

Citations5
Published2020
Admission routes2
Has abstractyes

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