Forensic neuropsychological assessment of children victims of violence
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
Violence in its most general aspect reveals important issues, mainly related to physical, mental, social and legal consequences. Childhood violence is a public health issue, as damage is described, affecting mainly cognitive, emotional and behavioral development. Studies show damage to children's development, resulting in biochemical, functional and structural changes in the brain, resulting from the violence suffered. The objective of the article was to verify the scientific production on the impact of violence on children's development in the field of forensic neuropsychology. Therefore, the production of knowledge on the topic and the impact of maltreatment on children's neuropsychological development was analyzed. This is an integrative literature review, supported by international databases. The results demonstrate the importance of a forensic neuropsychological assessment, to detect the impacts of violence, as well as to develop prevention and action strategies, in the scope of mental health, forensics and/or legal demands and thus, devise more effective measures for this population and subsidize public risk reduction policies applied to children and adolescents. Studies are still small, which shows a wide field to be investigated.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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