Health effects associated with exposure of children to physical violence, psychological violence and neglect: a Burden of Proof study
Classification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The health toll of child maltreatment or violence against children (VAC) has not yet been comprehensively evaluated. Here, in our systematic review and meta-analyses, we focused on the health impacts of physical violence, psychological violence and neglect during childhood. Utilizing the Burden of Proof methodology, which generates conservative measures of association while accounting for heterogeneity between input studies, we evaluated 35 associations between VAC and adverse health outcomes, identifying 27 statistically significant links. The associations between physical violence and major depressive disorder, ischaemic heart disease, alcohol use disorder, eating disorders and drug use disorders were rated as moderately weak, reflecting a small effect size and/or inconsistent evidence. The minimum increased risk ranged from 16% for depression to 2% for drug use disorders. Psychological violence showed similar moderately weak associations with drug use disorders (8% minimum risk increase), migraine (7%) and gynaecological diseases (2%). Neglect was linked to at least a 15% increased risk for anxiety disorders. The other 18 associations were weaker due to smaller effect sizes and/or less consistent evidence. Despite the limitations of the existing evidence, our analysis highlights substantial health impacts for VAC survivors, underscoring the need for health system prioritization and continued efforts to eliminate all forms of VAC.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it