Violence conjugale pendant la grossesse : recension des écrits
Bibliographic record
Abstract
La violence conjugale est un problème complexe dont l'ampleur et les conséquences sont de mieux en mieux documentées. Parmi les multiples facettes du phénomène, son occurrence pendant la grossesse suscite des inquiétudes particulières. Cet article fait le point sur les écrits scientifiques portant sur cette question. Après avoir traité de la prévalence de la violence conjugale pendant la grossesse, il rend compte des principales études qui ont analysé les facteurs associés à cette violence et de celles qui se sont intéressées à ses conséquences pour la mère et pour le bébé. L'article conclut que les informations actuelles, quoique partielles, sont suffisantes pour justifier le dépistage le plus hâtif possible de la présence de violence conjugale afin de venir en aide aux futures mères de façon appropriée.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".