Bibliographic record
Abstract
Résumé Cet article présente une revue de littérature sur les enfants ayant été témoins ou exposés à l’homicide conjugal. Des données statistiques provenant de différents pays (Australie, Canada, Israël, Afrique du Sud, États-Unis) montrent que de 40% à 70% des femmes victimes de meurtre ont été tuées par leur conjoint, ex-conjoint ou petit ami alors que ce n’est le cas que de 4% des hommes victimes de meurtres. Ces homicides conjugaux font de nombreuses victimes. Parmi elles, les enfants de ces couples, témoins ou exposés au meurtre. Les recherches portant sur les conséquences de l’homicide sur les enfants montrent que tous vivront des symptômes de stress post-traumatiques et ce, durant de nombreuses années après l’homicide. De plus, il semble que parmi eux, peu reçoivent des interventions appropriées à leur victimisation et que les effets du traumatisme peuvent être, dans certains cas, décuplés.
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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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
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".