A COMPREHENSIVE REVIEW OF THE LITERATURE ON THE IMPACT OF EXPOSURE TO INTIMATE PARTNER VIOLENCE FOR CHILDREN AND YOUTH
Bibliographic record
Abstract
<p><strong><strong><span style="font-family: Times New Roman;">Children living in homes </span></strong></strong><span style="font-family: Times New Roman;"><span style="font-size: medium;">where intimate partner violence occurs are often exposed to such violence through witnessing, seeing its effects, hearing about it, or otherwise being made aware that violence is taking place between parents or caregivers. Exposure to intimate partner violence is considered to be a form of child maltreatment, and affected children are often also the victims of targeted child abuse. This paper presents findings from a comprehensive review of the literature on the impact of exposure to intimate partner violence for children and youth, focusing on: (a) neurological disorders; (b) physical health outcomes; (c) mental health challenges; (d) conduct and behavioural problems; (e) delinquency, crime, and victimization; and (f) academic and employment outcomes. </span><span style="font-size: medium;">The notion of cascading effects informed our framework and analysis as it became evident that the individual categories of impacts were not only closely related to one another, but in a dynamic fashion also influence each other in multiple and interconnected ways over time</span><span style="font-size: medium;">. The research reviewed clearly shows that children who are exposed to intimate partner violence are at significant risk for lifelong negative outcomes, and the consequences are felt widely in society.</span></span></p>
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.015 |
| 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) | 0.004 | 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".