Pattern of hospital referrals of children at risk of maltreatment
Bibliographic record
Abstract
BACKGROUND: Increasingly emergency departments (ED) and other acute services in the hospital provide first access care, especially out of hours and for poorer families. Studies of detection of child maltreatment in the hospital have focused on children presenting with injury, although maltreatment may be suspected when parents present to the hospital with problems related to violent behaviour, drug abuse or mental health problems. METHODS: A consecutive case series is described of patients referred for suspected child maltreatment from one inner-city general hospital after training was given to clinical staff and 2 years after the creation of a new post comprising a full-time, experienced child protection advisor (CPA) on-site to support clinicians with concerns about child maltreatment. RESULTS: There were 44 referrals to the CPA over 2 months in 2005, of whom just under half were initiated by clinicians caring for a parent. 15 referrals came from the ED (five followed a parent presenting to the ED), 14 from maternity obstetric services, and 15 from the neonatal or paediatric wards. Most families (38; 86%) were referred by nurses. One-quarter of referrals were already known to children's social care. CONCLUSIONS: Clinicians need to be aware that half the vulnerable children in hospital are identified through one or other parent. It is hypothesised that the availability of an experienced child protection advisor on-site, combined with child protection training, makes it possible for clinicians caring for adults with problems related to violence, drug abuse or acute mental illness, to take action to address the potential vulnerability of their children.
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 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 | 0.000 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".